Analysis_bCLIP.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e74a5dee-53db-4ec8-b282-197067b4f82c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import (absolute_import, division,\n",
    "                        print_function, unicode_literals)\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter('ignore')\n",
    "\n",
    "# general purpose packages\n",
    "import pandas as pd\n",
    "import swifter # for parallelizing some pandas functions\n",
    "import numpy as np\n",
    "import os\n",
    "import json\n",
    "import time\n",
    "import re\n",
    "import csv\n",
    "import subprocess\n",
    "import sys\n",
    "import itertools\n",
    "\n",
    "import scipy.stats as stats\n",
    "import statsmodels.stats as smstats\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.stats.multitest import multipletests\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.decomposition import KernelPCA\n",
    "\n",
    "# for anomaly detection\n",
    "from sklearn.ensemble import IsolationForest\n",
    "import jenkspy\n",
    "\n",
    "# for scoring\n",
    "from scipy.stats import dirichlet\n",
    "from scipy import integrate\n",
    "\n",
    "import umap\n",
    "import rpy2\n",
    "\n",
    "from multiprocessing import Process, Manager, Pool\n",
    "import multiprocessing\n",
    "from functools import partial\n",
    "\n",
    "from collections import Counter\n",
    "\n",
    "import seaborn as sns; sns.set()\n",
    "\n",
    "import matplotlib\n",
    "matplotlib.style.use('seaborn')\n",
    "matplotlib.use('Agg')\n",
    "import matplotlib.pyplot as plt\n",
    "matplotlib.rcParams['backend'] = \"Qt5Agg\"\n",
    "import matplotlib.ticker as ticker\n",
    "from matplotlib.ticker import FuncFormatter\n",
    "\n",
    "from matplotlib.patches import Patch\n",
    "from matplotlib.lines import Line2D\n",
    "\n",
    "from IPython.display import display, Image\n",
    "\n",
    "from adjustText import adjust_text\n",
    "import builtins\n",
    "%matplotlib inline\n",
    "\n",
    "import textwrap\n",
    "\n",
    "# for normalization\n",
    "from sklearn.linear_model import QuantileRegressor\n",
    "\n",
    "# for custom clustering\n",
    "from scipy.cluster.hierarchy import linkage\n",
    "from scipy.spatial.distance import squareform\n",
    "from matplotlib.patches import Rectangle\n",
    "\n",
    "# for selecting combinations\n",
    "from itertools import combinations\n",
    "\n",
    "# for working with yaml files\n",
    "import ruamel.yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fa04c313-b1fa-4c17-a119-694602d8be02",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_pvalue_star(pval, thr=0.05):\n",
    "    if thr == 0.05:\n",
    "        if pval < 0.001:\n",
    "            return \"***\"\n",
    "        elif pval < 0.01:\n",
    "            return \"**\"\n",
    "        elif pval < 0.05:\n",
    "            return \"*\"\n",
    "        else:\n",
    "            return \"ns\"\n",
    "    elif thr == 0.1:\n",
    "        if pval < 0.001:\n",
    "            return \"***\"\n",
    "        elif pval < 0.01:\n",
    "            return \"**\"\n",
    "        elif pval < 0.1:\n",
    "            return \"*\"\n",
    "        else:\n",
    "            return \"ns\"\n",
    "\n",
    "from statsmodels.stats import proportion as smprop\n",
    "\n",
    "\n",
    "def get_group_percentages(df, x_group, hue, sum_by=None):\n",
    "    if sum_by is None:\n",
    "        grouped = df.groupby([hue], sort=False)\n",
    "        counts = grouped[x_group].value_counts(sort=False)\n",
    "        counts = pd.DataFrame(counts).rename(columns={x_group: \"count\"}).reset_index()\n",
    "\n",
    "        counts_sum = counts[[hue, \"count\"]].groupby(hue).sum()\n",
    "        counts_sum.reset_index(inpexperlace=True)\n",
    "        counts_sum.rename(columns={\"count\": \"countgroup\"}, inplace=True)\n",
    "\n",
    "        data = pd.merge(counts, counts_sum, how=\"left\", left_on=hue, right_on=hue)\n",
    "        data[\"percentage\"] = data[\"count\"] / data[\"countgroup\"] * 100\n",
    "    else:\n",
    "        grouped = (\n",
    "            df[[x_group, hue, sum_by]].groupby([hue, x_group], sort=False).agg(np.sum)\n",
    "        )\n",
    "        grouped.reset_index(inplace=True)\n",
    "\n",
    "        counts = grouped[[hue, sum_by]].groupby(hue).sum()\n",
    "        counts.reset_index(inplace=True)\n",
    "        counts = counts.rename(columns={sum_by: sum_by + \"_sumgroup\"})\n",
    "\n",
    "        data = pd.merge(grouped, counts, how=\"left\", left_on=hue, right_on=hue)\n",
    "        data[\"percentage\"] = data[sum_by] / data[sum_by + \"_sumgroup\"] * 100\n",
    "\n",
    "    return data.sort_values(by=[hue, x_group])\n",
    "\n",
    "\n",
    "def add_errorbars(ax_item, x, y, yerr):\n",
    "    yerr_0 = [0] * len(yerr)\n",
    "    yerr = [yerr_0, yerr]\n",
    "    (_, caps, _) = ax_item.errorbar(\n",
    "        x=x, y=y, yerr=yerr, capsize=3, fmt=\"none\", color=\"black\"\n",
    "    )\n",
    "    for cap in caps:\n",
    "        cap.set_markeredgewidth(1)\n",
    "\n",
    "\n",
    "def get_proportion_ci(data_percentage, data_observcount, z):\n",
    "    return (\n",
    "        100\n",
    "        * z\n",
    "        * ((data_percentage / 100) * (1 - data_percentage / 100) / (data_observcount))\n",
    "        ** 0.5\n",
    "    )\n",
    "\n",
    "\n",
    "def percentage_plot(\n",
    "    dataset,\n",
    "    x_group,\n",
    "    hue,\n",
    "    axes_pos=0,\n",
    "    legend_loc=\"upper right\",\n",
    "    cleanlook=False,\n",
    "    alpha=0.05,\n",
    "    palette=\"hls\",\n",
    "    dodge=0.52,\n",
    "    xlabel=\"\",\n",
    "    ylabel=\"\",\n",
    "    legend_title=\"\",\n",
    "    exclude_x_group=\"\",\n",
    "    point_scale=0,\n",
    "    edgecolor=\"black\",\n",
    "    linewidth=1,\n",
    "):\n",
    "\n",
    "    data = get_group_percentages(dataset, x_group, hue)\n",
    "\n",
    "    if exclude_x_group != \"\":\n",
    "        data = data.loc[~data[x_group].isin(exclude_x_group)]\n",
    "\n",
    "    palette_n = len(data[[hue]].drop_duplicates())\n",
    "\n",
    "    if axes_pos != 0:\n",
    "        ax0 = sns.pointplot(\n",
    "            x=x_group,\n",
    "            scale=point_scale,\n",
    "            y=\"percentage\",\n",
    "            hue=hue,\n",
    "            data=data,\n",
    "            ax=axes_pos,\n",
    "            palette=sns.color_palette(palette, palette_n),\n",
    "            #                          order = order,\n",
    "            dodge=dodge,\n",
    "            join=False,\n",
    "        )\n",
    "        ax0 = sns.barplot(\n",
    "            x=x_group,\n",
    "            y=\"percentage\",\n",
    "            hue=hue,\n",
    "            data=data,\n",
    "            ax=axes_pos,\n",
    "            palette=sns.color_palette(palette, palette_n),\n",
    "            linewidth=linewidth,\n",
    "            edgecolor=edgecolor,\n",
    "            #                          order = order\n",
    "        )\n",
    "    else:\n",
    "        ax0 = sns.pointplot(\n",
    "            x=x_group,\n",
    "            scale=point_scale,\n",
    "            y=\"percentage\",\n",
    "            hue=hue,\n",
    "            data=data,\n",
    "            palette=sns.color_palette(palette, palette_n),\n",
    "            #                          order = order,\n",
    "            dodge=dodge,\n",
    "            join=False,\n",
    "        )\n",
    "        ax0 = sns.barplot(\n",
    "            x=x_group,\n",
    "            y=\"percentage\",\n",
    "            hue=hue,\n",
    "            data=data,\n",
    "            palette=sns.color_palette(palette, palette_n),\n",
    "            linewidth=linewidth,\n",
    "            edgecolor=edgecolor,\n",
    "            #                          order = order\n",
    "        )\n",
    "    x_coords = []\n",
    "    y_coords = []\n",
    "    for point_pair in ax0.collections:\n",
    "        for x, y in point_pair.get_offsets():\n",
    "            x_coords.append(x)\n",
    "            y_coords.append(y)\n",
    "    try:\n",
    "        add_errorbars(\n",
    "            ax0,\n",
    "            x=x_coords,\n",
    "            y=y_coords,\n",
    "            yerr=(\n",
    "                data.apply(\n",
    "                    lambda x: smprop.proportion_confint(\n",
    "                        count=x[\"count\"],\n",
    "                        nobs=x[\"countgroup\"],\n",
    "                        alpha=alpha,\n",
    "                        method=\"normal\",\n",
    "                    )[1],\n",
    "                    1,\n",
    "                )\n",
    "                - data[\"percentage\"] / 100\n",
    "            )\n",
    "            * 100,\n",
    "        )\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "\n",
    "    if legend_loc == None:\n",
    "        legend = ax0.legend()\n",
    "        legend.remove()\n",
    "    elif legend_loc == \"outside\":\n",
    "        leg_handles = ax0.get_legend_handles_labels()[0][\n",
    "            len(data[hue].drop_duplicates()) :\n",
    "        ]\n",
    "        ax0.legend(\n",
    "            leg_handles,\n",
    "            list(data[hue].drop_duplicates().sort_values()),\n",
    "            bbox_to_anchor=(1.05, 1),\n",
    "            loc=2,\n",
    "            title=legend_title,\n",
    "            borderaxespad=0.0,\n",
    "        )\n",
    "    else:\n",
    "        leg_handles = ax0.get_legend_handles_labels()[0][\n",
    "            len(data[hue].drop_duplicates()) :\n",
    "        ]\n",
    "        ax0.legend(\n",
    "            leg_handles,\n",
    "            list(data[hue].drop_duplicates().sort_values()),\n",
    "            title=legend_title,\n",
    "            loc=legend_loc,\n",
    "        )\n",
    "\n",
    "    if cleanlook:\n",
    "        ax0.set(ylabel=\"\", xlabel=\"\")\n",
    "        ax0.legend_.remove()\n",
    "    if ylabel != \"\":\n",
    "        ax0.set(ylabel=ylabel)\n",
    "    if xlabel != \"\":\n",
    "        ax0.set(xlabel=xlabel)\n",
    "    return ax0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ca9453f4-cde2-4288-9c53-d0dba36721a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# paths to subdirectories\n",
    "subdirs = {}\n",
    "\n",
    "subdirs['main_project_dir'] = '/scicore/home/zavolan/GROUP/StefanieCLIP/'\n",
    "subdirs['wf_dir'] = '/scicore/home/zavolan/mirono0000/Projects/bCLIP/bclip_workflow/'\n",
    "\n",
    "subdirs['zarp_dir'] = '/scicore/home/zavolan/mirono0000/libs/zarp/'\n",
    "subdirs['htsinfer_dir'] = '/scicore/home/zavolan/mirono0000/libs/htsinfer/'\n",
    "subdirs['zarp_config_dir'] = subdirs['zarp_dir']+'config/'\n",
    "\n",
    "subdirs['mouse_annotation_dir'] = '/scicore/home/zavolan/GROUP/Genomes/mus_musculus/'\n",
    "subdirs['human_annotation_dir'] = '/scicore/home/zavolan/GROUP/Genomes/homo_sapiens/'\n",
    "\n",
    "# shared project folder \n",
    "subdirs['shared_project_dir'] = subdirs['main_project_dir']+'aleksei/'\n",
    "subdirs['temp_dir'] = subdirs['shared_project_dir']+'temp_dir/'\n",
    "subdirs['slurm_dir'] = subdirs['temp_dir']+'slurm/'\n",
    "subdirs['scripts_dir'] = subdirs['shared_project_dir']+'scripts/'\n",
    "subdirs['figures_dir'] = subdirs['shared_project_dir']+'figures/'\n",
    "subdirs['tables_dir'] = subdirs['shared_project_dir']+'tables/'\n",
    "\n",
    "subdirs['fastq_dir'] = subdirs['shared_project_dir']+'input_fastq/'\n",
    "subdirs['metadata_dir'] = subdirs['shared_project_dir']+'metadata/'\n",
    "subdirs['wf_output_dir'] = subdirs['shared_project_dir']+'output/'\n",
    "\n",
    "# paths to files\n",
    "file_paths = {}\n",
    "### genome annotation files\n",
    "file_paths['mouse_genome_file'] = subdirs['mouse_annotation_dir']+'GRCm39.primary_assembly.genome.fa'\n",
    "file_paths['mouse_annotation_file'] = subdirs['mouse_annotation_dir']+'gencode.vM32.annotation.gtf'\n",
    "file_paths['mouse_RNAcentral_annotation_file'] = subdirs['mouse_annotation_dir']+'mus_musculus.GRCm39.gff3.gz'\n",
    "file_paths['mouse_FeatureCounts_gtf_file'] = subdirs['mouse_annotation_dir']+'exonic_segments.gtf'\n",
    "\n",
    "file_paths['mouse_prot_coding_gtf'] = subdirs['mouse_annotation_dir']+'coding.gencode.vM32.annotation.gtf'\n",
    "file_paths['mouse_collapsed_prot_coding_gtf'] = subdirs['mouse_annotation_dir']+'collapsed.coding.gencode.vM32.annotation.gtf'\n",
    "\n",
    "file_paths['mouse_enriched_annotation_file'] = subdirs['mouse_annotation_dir']+'enriched.gencode.vM32.annotation.gtf' # added RNA species from RNA central\n",
    "file_paths['mouse_collapsed_enriched_annotation_file'] = subdirs['mouse_annotation_dir']+'collapsed.enriched.gencode.vM32.annotation.gtf'\n",
    "\n",
    "file_paths['human_genome_file'] = subdirs['human_annotation_dir']+'GRCh38.primary_assembly.genome.fa'\n",
    "file_paths['human_annotation_file'] = subdirs['human_annotation_dir']+'hg38_v42/gencode.v42.annotation.gtf'\n",
    "file_paths['human_RNAcentral_annotation_file'] = subdirs['human_annotation_dir']+'hg38_v42/homo_sapiens.GRCh38.gff3.gz'\n",
    "file_paths['human_FeatureCounts_gtf_file'] = subdirs['human_annotation_dir']+'hg38_v42/exonic_segments.gtf'\n",
    "\n",
    "file_paths['human_enriched_annotation_file'] = subdirs['human_annotation_dir']+'hg38_v42/enriched.gencode.v42.annotation.gtf'\n",
    "\n",
    "file_paths['htsinfer_transcripts_file'] = '/scicore/home/zavolan/GROUP/Genomes/htsinfer_deduplicated_transcripts.fasta'\n",
    "\n",
    "### control data\n",
    "file_paths['control_metadata_file_1'] = subdirs['metadata_dir']+'SRA_CONTROL_DATA_1.tsv'\n",
    "file_paths['control_metadata_file_2'] = subdirs['metadata_dir']+'SRA_CONTROL_DATA_2.tsv'\n",
    "\n",
    "os.system('mkdir -p '+' '.join(list(subdirs.values()))) # create all subdirs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d07a5bfe-444d-4ee3-9231-6661f04c83c5",
   "metadata": {},
   "source": [
    "# bCLIP analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f68123fa-85f7-45fe-841d-03de2498a3e1",
   "metadata": {},
   "source": [
    "## Check that NRDE bCLIP matches the NRDE from original paper and separates from Ints bCLIPs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5fa0c5bb-348f-481a-90a2-c072b2a4ffa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "experimental_bCLIP_samples = pd.read_csv(subdirs['metadata_dir']+'experimental_bCLIP_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "public_bCLIP_and_ChipSeq_samples = pd.read_csv(subdirs['metadata_dir']+'public_bCLIP_and_ChipSeq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "bclip_experiments_to_analyze = ['RBC_exp17','RBC_exp18','Ints11C_replicate5','Ints11C_replicate6','Ints10N_replicate1','Ints10N_replicate2']\n",
    "\n",
    "experimental_bCLIP_samples['type'] = 'in-house'\n",
    "public_bCLIP_and_ChipSeq_samples['type'] = 'public'\n",
    "\n",
    "samples_to_analyze_df = pd.concat([experimental_bCLIP_samples.loc[experimental_bCLIP_samples['name'].isin(bclip_experiments_to_analyze)][['name','type','condition_name']],\n",
    "                                  public_bCLIP_and_ChipSeq_samples.loc[(public_bCLIP_and_ChipSeq_samples['batch']=='public_bCLIP_mESC')&(\n",
    "                                      public_bCLIP_and_ChipSeq_samples['condition_name']!='Mtrex')][['name','type','condition_name']]]).reset_index(drop=True)\n",
    "samples_to_analyze_df['condition'] = samples_to_analyze_df['condition_name']+'; '+samples_to_analyze_df['type']\n",
    "\n",
    "plot_specification = samples_to_analyze_df[['condition']].drop_duplicates().reset_index(drop=True)\n",
    "plot_specification['color'] = ['darkturquoise','olive','grey','orange','blue','gold','green','greenyellow']\n",
    "\n",
    "samples_to_analyze_df = samples_to_analyze_df[['name','condition']].rename(columns = {'name':'sample'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "037f873b-0639-4a9d-9d6d-757523e66ffc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ints11C_replicate5 done\n",
      "Ints11C_replicate6 done\n",
      "Ints10N_replicate1 done\n",
      "Ints10N_replicate2 done\n",
      "RBC_exp17 done\n",
      "RBC_exp18 done\n",
      "SRR15070630 done\n",
      "SRR15070631 done\n",
      "SRR15070632 done\n",
      "SRR15070633 done\n",
      "SRR15070635 done\n",
      "SRR15070636 done\n",
      "SRR15070639 done\n",
      "SRR15070640 done\n",
      "SRR15070642 done\n",
      "SRR15070643 done\n"
     ]
    }
   ],
   "source": [
    "i = 0\n",
    "a = []\n",
    "for index,row in samples_to_analyze_df.iterrows():\n",
    "    sample = row['sample']\n",
    "    file_path = subdirs['wf_output_dir']+'samples/'+sample+'/segment_counts_all/exon_intron/'+sample+'.wd_counts.tsv'\n",
    "\n",
    "    if i==0:\n",
    "        tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,usecols=[0,1,2,3,5])\n",
    "        tmp[['chr','strand']] = tmp[['chr','strand']].astype('category')\n",
    "        tmp = tmp.rename(columns = {'uniquely_mapped;0':sample})\n",
    "    else:\n",
    "        tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,usecols=[5])\n",
    "        tmp = tmp.rename(columns = {'uniquely_mapped;0':sample})\n",
    "    a.append(tmp)\n",
    "    print(sample+' done')\n",
    "    i=i+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0d7652e3-b7c6-41e2-9b82-4de7ba5359e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "wd_counts = pd.concat(a,axis=1)\n",
    "sample_list = list(samples_to_analyze_df['sample'])\n",
    "wd_counts['sum'] = wd_counts[sample_list].sum(1)\n",
    "wd_counts = wd_counts.loc[wd_counts['sum']>0].reset_index(drop=True)\n",
    "wd_counts[sample_list] = wd_counts[sample_list]+1 # pseudocount of 1\n",
    "# convert to CPM\n",
    "wd_counts[sample_list] = ((wd_counts[sample_list])*(10**6)).div(wd_counts[sample_list].sum())\n",
    "wd_counts[sample_list] = np.log2(wd_counts[sample_list])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "14571d94-d2ef-4aa3-8db3-403131330630",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = (wd_counts.loc[wd_counts['sum']>wd_counts['sum'].quantile(0.98)][sample_list].values).transpose()\n",
    "x = StandardScaler().fit_transform(x)\n",
    "\n",
    "pca = PCA(n_components=2)\n",
    "principalComponents = pca.fit_transform(x)\n",
    "principalDf = pd.DataFrame(data = principalComponents, columns = ['PC1', 'PC2'])\n",
    "principalDf['sample'] = sample_list\n",
    "\n",
    "principalDf = pd.merge(principalDf,samples_to_analyze_df,how='left',on='sample')\n",
    "\n",
    "x_feature,y_feature = 'PC1','PC2'\n",
    "bw_adjust = 1.75\n",
    "alpha_param, s_param = 0.7, 80\n",
    "\n",
    "hue='condition'\n",
    "hue_order = list(plot_specification[hue])\n",
    "palette = list(plot_specification['color'])\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(4,4))\n",
    "\n",
    "ax = sns.scatterplot(data = principalDf,x=x_feature,y=y_feature,s=s_param,alpha=alpha_param,edgecolor='black',linewidth=0.5,\n",
    "                     hue=hue,hue_order = hue_order, palette = palette)\n",
    "ax.legend(bbox_to_anchor=(1.05, 1),loc=2,borderaxespad=0.0,title='')\n",
    "ax.set(xlabel = 'PC1, '+str(int(np.round(pca.explained_variance_ratio_[0]*100,0)))+'% variance')\n",
    "ax.set(ylabel = 'PC2, '+str(int(np.round(pca.explained_variance_ratio_[1]*100,0)))+'% variance')\n",
    "ax.set(title = 'TPM of top ~'+str(int(np.shape(x)[1]/1000))+'k genomic segments\\nby average expression')\n",
    "\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'Reproducibility/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'Reproducibility/PCA_without_in_house_NRDE2_and_Mtrex.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'Reproducibility/PCA_without_in_house_NRDE2_and_Mtrex.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3834ad14-1743-4f28-95ec-4cefa6d61dc5",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Make nice metaplots for Ints11C, Ints10N, RBC, eCLIP (Hela)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "8ed3a20e-16c9-4d63-8c8b-737afbf97a47",
   "metadata": {},
   "outputs": [],
   "source": [
    "experimental_bCLIP_samples = pd.read_csv(subdirs['metadata_dir']+'experimental_bCLIP_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "public_bCLIP_and_ChipSeq_samples = pd.read_csv(subdirs['metadata_dir']+'public_bCLIP_and_ChipSeq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "experiments_to_analyze = ['RBC_exp17','Ints11C_replicate5','Ints10N_replicate1','SRR11551259','SRR11551261']\n",
    "# experiments_to_analyze = ['RBC_exp17','Ints11C_replicate5','Ints10N_replicate1','SRR11551259','SRR11551261']\n",
    "\n",
    "experimental_bCLIP_samples['type'] = 'in-house bCLIP'\n",
    "public_bCLIP_and_ChipSeq_samples['type'] = 'public eCLIP'\n",
    "\n",
    "samples_to_analyze_df = pd.concat([experimental_bCLIP_samples.loc[experimental_bCLIP_samples['name'].isin(experiments_to_analyze)][['name','type','condition_name']],\n",
    "                                  public_bCLIP_and_ChipSeq_samples.loc[(public_bCLIP_and_ChipSeq_samples['name'].isin(experiments_to_analyze))][['name','type','condition_name']]]).reset_index(drop=True)\n",
    "samples_to_analyze_df['condition'] = samples_to_analyze_df['condition_name']+'; '+samples_to_analyze_df['type']\n",
    "\n",
    "plot_specification = samples_to_analyze_df[['condition']].drop_duplicates().reset_index(drop=True)\n",
    "plot_specification['color'] = ['darkturquoise','olive','grey','cyan','magenta']\n",
    "\n",
    "samples_to_analyze_df = samples_to_analyze_df[['name','condition']].rename(columns = {'name':'sample'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "d09834f1-9d29-48d6-9d3f-30b17eacf6ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.03081821458608675, 0.03256145514751535)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1026/(1026+2196+4057+5219+20794),1416/(1416+2964+5083+4851+29173)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "09ac2ed4-f267-441a-bf09-191be03739c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_feature,y_feature = 'pos_rel_to_TSS','mean'\n",
    "expr_cat = ''\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(5,3),)\n",
    "\n",
    "i=0\n",
    "for index,row in samples_to_analyze_df.iterrows():\n",
    "    sample = row['sample']\n",
    "    condition = row['condition']\n",
    "    color = plot_specification.loc[plot_specification['condition']==condition].iloc[0]['color']\n",
    "    \n",
    "    file_path = subdirs['wf_output_dir']+'samples/'+sample+'/segment_counts_all/metaplot/'+sample+'.1.uniquely_mapped_0.metaplot_density.tsv'\n",
    "    tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "    # take the highest category if not RBC\n",
    "    if condition!='RBC; in-house bCLIP':\n",
    "        l = list(tmp['expr_cat'].unique())\n",
    "        l.sort()\n",
    "        tmp = tmp.loc[tmp['expr_cat']==l[-1]].reset_index(drop=True)\n",
    "    else:\n",
    "        k = [32985,220,69,17,1]\n",
    "        k[0]=int(sum(k)*0.03)-sum(k[1:])\n",
    "        summa = sum(k)\n",
    "        w = [elem/summa for elem in k]\n",
    "        weights_df = pd.DataFrame([list(tmp['expr_cat'].unique()),w]).transpose()\n",
    "        weights_df.columns = ['expr_cat','w']\n",
    "        tmp = pd.merge(tmp,weights_df,how='left',on='expr_cat')\n",
    "        tmp[y_feature] = tmp[y_feature]*tmp['w']\n",
    "        tmp=tmp.groupby(x_feature).agg({y_feature:np.mean}).reset_index()\n",
    "    ax = sns.lineplot(data = tmp,x=x_feature,y=y_feature,color=color,label=condition)\n",
    "    \n",
    "    i=i+1\n",
    "ax.set(title='mean read density around\\ntop 3% TSS with highest expression',ylabel='',xlabel='position relative to TSS')\n",
    "ymin,ymax = ax.get_ylim()[0],ax.get_ylim()[1]\n",
    "ax.vlines(x=0,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.vlines(x=150,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.vlines(x=-150,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.text(-150,-0.001,'-150',ha='right',va='center',size=10)\n",
    "ax.text(150,-0.001,'+150',ha='left',va='center',size=10)\n",
    "\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "\n",
    "ax.legend(bbox_to_anchor=(1.05, 1),loc=2,borderaxespad=0.0,title='')\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'Reproducibility/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'Reproducibility/Metaplots.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'Reproducibility/Metaplots.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "88ffbdbf-4ece-44c0-97b7-7fd60fc50482",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_feature,y_feature = 'pos_rel_to_TSS','median'\n",
    "expr_cat = ''\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(5,3),)\n",
    "\n",
    "i=0\n",
    "for index,row in samples_to_analyze_df.iterrows():\n",
    "    sample = row['sample']\n",
    "    condition = row['condition']\n",
    "    color = plot_specification.loc[plot_specification['condition']==condition].iloc[0]['color']\n",
    "    \n",
    "    file_path = subdirs['wf_output_dir']+'samples/'+sample+'/segment_counts_all/metaplot/'+sample+'.1.uniquely_mapped_0.metaplot_density.tsv'\n",
    "    tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "    # take the highest category if not RBC\n",
    "    if condition!='RBC; in-house bCLIP':\n",
    "        l = list(tmp['expr_cat'].unique())\n",
    "        l.sort()\n",
    "        tmp = tmp.loc[tmp['expr_cat']==l[-1]].reset_index(drop=True)\n",
    "    else:\n",
    "        k = [32985,220,69,17,1]\n",
    "        k[0]=int(sum(k)*0.03)-sum(k[1:])\n",
    "        summa = sum(k)\n",
    "        w = [elem/summa for elem in k]\n",
    "        weights_df = pd.DataFrame([list(tmp['expr_cat'].unique()),w]).transpose()\n",
    "        weights_df.columns = ['expr_cat','w']\n",
    "        tmp = pd.merge(tmp,weights_df,how='left',on='expr_cat')\n",
    "        tmp[y_feature] = tmp[y_feature]*tmp['w']\n",
    "        tmp=tmp.groupby(x_feature).agg({y_feature:np.mean}).reset_index()\n",
    "    ax = sns.lineplot(data = tmp,x=x_feature,y=y_feature,color=color,label=condition)\n",
    "    \n",
    "    i=i+1\n",
    "ax.set(title='median read density around\\ntop 3% TSS with highest expression',ylabel='',xlabel='position relative to TSS')\n",
    "ymin,ymax = ax.get_ylim()[0],ax.get_ylim()[1]\n",
    "ax.vlines(x=0,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.vlines(x=150,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.vlines(x=-150,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.text(-150,-0.0004,'-150',ha='right',va='center',size=10)\n",
    "ax.text(150,-0.0004,'+150',ha='left',va='center',size=10)\n",
    "\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "\n",
    "ax.legend(bbox_to_anchor=(1.05, 1),loc=2,borderaxespad=0.0,title='')\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'Reproducibility/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'Reproducibility/Metaplots_median.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'Reproducibility/Metaplots_median.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0f6e47b-48af-4a15-910f-052a9946d43d",
   "metadata": {},
   "source": [
    "## Make quantification for Ints11C, Ints10N, RBC, eCLIP (Hela)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dbed5df8-e998-427f-8f3e-bc47672b6383",
   "metadata": {},
   "outputs": [],
   "source": [
    "experimental_bCLIP_samples = pd.read_csv(subdirs['metadata_dir']+'experimental_bCLIP_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "public_bCLIP_and_ChipSeq_samples = pd.read_csv(subdirs['metadata_dir']+'public_bCLIP_and_ChipSeq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "experiments_to_analyze = ['RBC_exp17','RBC_exp18','Ints11C_replicate5','Ints11C_replicate6','Ints10N_replicate1','Ints10N_replicate2',\n",
    "                          'SRR11551259','SRR11551260','SRR11551261','SRR11551262']\n",
    "\n",
    "experimental_bCLIP_samples['type'] = 'in-house bCLIP'\n",
    "public_bCLIP_and_ChipSeq_samples['type'] = 'public eCLIP'\n",
    "\n",
    "samples_to_analyze_df = pd.concat([experimental_bCLIP_samples.loc[experimental_bCLIP_samples['name'].isin(experiments_to_analyze)][['name','type','condition_name','batch']],\n",
    "                                  public_bCLIP_and_ChipSeq_samples.loc[(public_bCLIP_and_ChipSeq_samples['name'].isin(experiments_to_analyze))][['name','type','condition_name','batch']]]).reset_index(drop=True)\n",
    "samples_to_analyze_df['condition'] = samples_to_analyze_df['condition_name']+'; '+samples_to_analyze_df['type']\n",
    "samples_to_analyze_df['organism'] = samples_to_analyze_df.apply(lambda x:'human' if ('Hela' in x['batch']) else 'mouse',1)\n",
    "\n",
    "plot_specification = samples_to_analyze_df[['condition']].drop_duplicates().reset_index(drop=True)\n",
    "plot_specification['color'] = ['darkturquoise','olive','grey','cyan','magenta']\n",
    "\n",
    "samples_to_analyze_df = samples_to_analyze_df[['name','condition','organism']].rename(columns = {'name':'sample'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9e9abce7-7fb5-40d9-8da5-f3db8767c64a",
   "metadata": {},
   "outputs": [],
   "source": [
    "organisms = list(samples_to_analyze_df['organism'].unique())\n",
    "cl = []\n",
    "for organism in organisms:\n",
    "    enriched_gtf = pd.read_csv(file_paths[organism+'_enriched_annotation_file'],delimiter=\"\\t\",\n",
    "                                       index_col=None,header=None,usecols = [0])\n",
    "    chromosome_list =  list(enriched_gtf[0].unique())\n",
    "    cl.append([organism,' '.join(chromosome_list)])\n",
    "cl = pd.DataFrame(cl,columns=['organism','chromosomes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "599f72fe-f66b-47fe-a15d-b587012400e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mouse, chr1 done\n",
      "mouse, chr2 done\n",
      "mouse, chr3 done\n",
      "mouse, chr4 done\n",
      "mouse, chr5 done\n",
      "mouse, chr6 done\n",
      "mouse, chr7 done\n",
      "mouse, chr8 done\n",
      "mouse, chr9 done\n",
      "mouse, chr10 done\n",
      "mouse, chr11 done\n",
      "mouse, chr12 done\n",
      "mouse, chr13 done\n",
      "mouse, chr14 done\n",
      "mouse, chr15 done\n",
      "mouse, chr16 done\n",
      "mouse, chr17 done\n",
      "mouse, chr18 done\n",
      "mouse, chr19 done\n",
      "mouse, chrX done\n",
      "mouse, chrY done\n",
      "mouse, chrM done\n",
      "human, chr1 done\n",
      "human, chr2 done\n",
      "human, chr3 done\n",
      "human, chr4 done\n",
      "human, chr5 done\n",
      "human, chr6 done\n",
      "human, chr7 done\n",
      "human, chr8 done\n",
      "human, chr9 done\n",
      "human, chr10 done\n",
      "human, chr11 done\n",
      "human, chr12 done\n",
      "human, chr13 done\n",
      "human, chr14 done\n",
      "human, chr15 done\n",
      "human, chr16 done\n",
      "human, chr17 done\n",
      "human, chr18 done\n",
      "human, chr19 done\n",
      "human, chr20 done\n",
      "human, chr21 done\n",
      "human, chr22 done\n",
      "human, chrX done\n",
      "human, chrY done\n",
      "human, chrM done\n"
     ]
    }
   ],
   "source": [
    "counts = {}\n",
    "for index1,row1 in cl.iterrows():\n",
    "    organism = row1['organism']\n",
    "    chromosomes = row1['chromosomes'].split(' ')\n",
    "    a1 = []\n",
    "    for chromosome in chromosomes:\n",
    "        i=0\n",
    "        a = []\n",
    "        for index,row in samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism].iterrows():\n",
    "            sample = row['sample']\n",
    "            file_path = subdirs['wf_output_dir']+'samples/'+sample+'/segment_counts_all/sel_TSSs/'+sample+'.'+chromosome+'.wd_counts.tsv'\n",
    "            if i==0:\n",
    "                tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,usecols = [0,3,4,5])\n",
    "            else:\n",
    "                tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,usecols=[5])\n",
    "            tmp = tmp.rename(columns = {'uniquely_mapped;0':sample})\n",
    "            a.append(tmp)\n",
    "            i=i+1\n",
    "        a = pd.concat(a,axis=1)\n",
    "        a1.append(a)\n",
    "        print(organism+', '+chromosome+' done')\n",
    "    a1 = pd.concat(a1).reset_index(drop=True)\n",
    "    a1[['chr','strand']] = a1[['chr','strand']].astype('category')\n",
    "    counts[organism] = a1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b7b9e7dc-e489-4842-8e0c-e5ce64930088",
   "metadata": {},
   "outputs": [],
   "source": [
    "organism = 'human'\n",
    "segments_of_interest = ['signal','control_up']\n",
    "samples_list = list(samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism]['sample'])\n",
    "\n",
    "df = counts[organism]\n",
    "df[samples_list] = df[samples_list].astype('int')\n",
    "df['TSS'] = df.apply(lambda x:x['segment_name'].split(';')[-1]+';'+x['segment_name'].split(';')[1],1)\n",
    "df['segment'] = df.apply(lambda x:x['segment_name'].split(';')[0],1).astype('category')\n",
    "df = df.loc[df['segment'].isin(segments_of_interest)].reset_index(drop=True)\n",
    "\n",
    "pivot = pd.pivot_table(df,index=['TSS','chr','strand'],columns='segment',values = samples_list).reset_index()\n",
    "columns = []\n",
    "for elem in pivot.columns:\n",
    "    columns.append(';'.join(elem) if elem[1]!='' else elem[0])\n",
    "pivot.columns = columns\n",
    "\n",
    "a = []\n",
    "for sample in samples_list:\n",
    "    values = pivot[list(sample+';'+pd.Series(segments_of_interest))].drop_duplicates().reset_index(drop=True)\n",
    "    values.columns = segments_of_interest\n",
    "    a.append(values)\n",
    "values = pd.concat(a).drop_duplicates().reset_index(drop=True)\n",
    "values['sum'] = values[segments_of_interest].sum(1)\n",
    "values['pval'] = values.apply(lambda x:stats.binomtest(k=x[segments_of_interest[0]],n=x['sum'],p=0.5,alternative='greater').pvalue if x['sum']>0 else 1,1)\n",
    "values['lfc'] = np.log2((values[segments_of_interest[0]]+1)/(values[segments_of_interest[1]]+1))\n",
    "values['average_log2'] = np.log2(values['sum']+1)\n",
    "for sample in samples_list:\n",
    "    pivot = pd.merge(pivot,values.drop('sum',1).rename(columns={segments_of_interest[0]:sample+';'+segments_of_interest[0],\n",
    "                       segments_of_interest[1]:sample+';'+segments_of_interest[1],\n",
    "                      'pval':sample+';pval','lfc':sample+';lfc','average_log2':sample+';average_log2'}),how='left',on=[sample+';'+segments_of_interest[0],sample+';'+segments_of_interest[1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1c9fe4a3-873c-44c7-b922-b7360c51ad14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "70139"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pivot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "165a3cd5-6b54-402d-a817-75ef317f912d",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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epFAoai0xv5Gjo6O0PFoQBEGonwiGBEEQBEF4oImcIeGB1LVrVxQKxV3RKkMQhNpycnIwNDTk5MmTd/pWhAeACIaEB1JVVRVKpfJO34YgCPWoqalpclVtQWguEQwJDyRt3yVRAE4Q7k43WyAgCC1JrLsVBEEQBOGBJoIhQRAEQRAeaGKaTGgVEydO5Pjx43U+98033/DYY4816bjt27fj6+vbovcoCIIgCCCCIaGV/Oc//6G0tFRn29KlS9m9ezc9e/Zs8NjQ0FDeeustnW1t2rRp8XsUBEEQBBDBkNBK/Pz8am3717/+xUMPPYStrW2Dx1paWtKpU6dWujNBEARB0CVyhoTbIjo6mqtXrzJs2LA7fSuCIAiCoEOMDAm3xdatWzExMWnUctnjx4/TqVMnlEolHTt25OWXX6Zbt25NvmZD18rMzMTFxaXJ5xQEQRDuPyIYElpdTU0NO3fuZMCAAZiamja4b7du3RgxYgReXl5kZ2ezePFipkyZwvLly+ncufNtumNBuAPKKiGvACzMwMbyTt+NIDxQRDAktLrDhw+Tl5dHRETETfd96aWXdB7369ePiIgIFi5cyC+//NKk6zZUUFEUdBPuOmmZcC0P9PSgezAYGd7pOxKEB4bIGRJa3datW7G2tiY8PLzJx5qamtK3b1/Onz/fCncmCHcRg/99NjUyAD3Znb0XQXjAiJEhoVVVVlayd+9ehg0bhoGBQbPOIfoTCQ8EDxewsgBTY2jmz4ogCM0jgiGhVe3bt4+ysrJmryIrLy8nMjKSDh06tPCdCcJdxkAf7K3v9F0IwgNJBENCq9qyZQuurq506dKl1nPvvPMOmzZtIi4uDoCTJ0+yePFiBg4ciKurK9nZ2SxZsoScnBy+/fbb233rgiAIwgNCBENCqykqKuLQoUNMmjQJmax2DoRKpUKpVEqPHRwcUCgUfPPNNxQWFmJiYkLnzp358MMPCQkJuZ23LgiCIDxAZGqRkCE8gLSryRpacSYIwp0jfkaF20msJhMEQRAE4YEmgiFBEARBEB5oIhgSBEEQBOGBJoIhQRAEQRAeaCIYEgRBEAThgSaCIUEQBEEQHmgiGBIEQRAE4YEmgiFBEARBEB5oIhgSBEEQBOGBJoIhQRCEphBF+wXhviN6kwmCIDRWUSkkXAETI2jrDoaGd/qOBEFoAWJkSBAEobEKiqCsHHILoLTi9l23rBIuJsPlNKiuvn3XFYQHhAiGBEEQGlJVBaXlmq9trDSjQrZWYG56++4hrwCu5UH6Nc3olCAILUpMkwmCINSnqAQupkCVAnzdwc0RugaBTKb5c7tYmoNcD4wMwNTk9l1XEB4QIhgSBEGoS34RZOdDZZXmcXGpJhjSuwMD6tYW0L2DJgAzEG/bgtDSxE+VIAhCXYpKNflBDrZQUwOOtnf2fgwN7uz1BeE+JoIhQRAErYISyMzWjL442GqCIUMD8PcAffF2KQj3K/HTLQiCAKBUQnoW5BVpHltZQHDbO3tPgiDcFiIYEgThwaZUaqbEDPQ1OTlyuSZZ2cz4Tt+ZIAi3iQiGBEF4sKVnQ3K6Zjqsnff/ls2bgdltXDovCMIdJYIhQRAebIr/FTGsrtEsXbexvLP3IwjCbSeCIUEQHiwqlSYvqKZGkyTt5qiZIjMzETV8BOEBJYIhQRAeHFUKSEmHnALNCJBaDa6O4Ol6p+9MEIQ7SLTjEAThwZGTD9kFoFRBRRXIxedBQRDEyJAgCA+CzFxNby8zE7C1hPJKTRFFB+s7fWeCINwFxMiQ0Co2bNhAQEBArT9fffXVTY/duHEjgwcPpkOHDkRERLBjx47bcMfCfamiAi6laBqdmhpCXqFmeizAGzxc7kxrDUEQ7jpiZEhoVb/++isWFhbSYycnpwb337lzJ3PmzOG5557joYce4u+//+bVV1/FwsKC8PDw1r5d4X6iUkFWHmTlah7b24CFKTjZaWoJNVWVQhNMmZloCjIKgnDfEMGQ0KqCgoKwtW18T6dvv/2WwYMH869//QuAsLAwkpOT+e6770QwJDReUSlcyQRzE81KseoaMDECD+fmBUIAaVmamkRyPegWBEZGLXvPgiDcMWKMWLhrpKWlkZSUREREhM72iIgIYmJiyM/Pv0N3JtxzcvI1XeevZIG7M7T1BJ82t9ZfTE/2v7/1AFmL3KYgCHcHMTIktKqIiAgKCgpwdXVl3LhxTJ8+HXk9n8yTkpIA8PHx0dnu6+uLWq0mKSmpSaNMAwYMqPe5zMxMXFxcGn0u4R5QVaUZATI300xjZeSAtblmWqwlOr63cdbUITIzASPDWz+fIAh3DREMCa3CwcGBF198kY4dOyKTydi3bx/z58/n2rVrvP/++3UeU1SkaZBpaalbAdjKykrneUGopbQcLiRChQJ83DSBi1WIZkqrOdNiFZVQWgFWZmD4v8DH0ACc7Vv2vgVBuCuIYEhoFb1796Z3797S4/DwcIyMjFi6dCnPP/88jo6O9R4rk+lOQajV6jq338zevXvrfa6hUSPhHpOSDjVKKK/SPC4u0/zd3NEgpRIuJEFJuSb4CfBqkdsUBOHuJXKGhNtmyJAhKJVKLly4UOfz9Y0AFRcXA7VHjIQHXHU1ZGRDaqamorSjraaGkGPjp1LrpFJD1f/6lWn7lgmCcF8TI0PCXUObK5SUlISvr6+0PTExEZlMViuXSHiAFRZBahYoFJq6QQXFmsTmDv63fm4DfQj00axIs7O69fMJgnDXEyNDwm2zfft25HI5gYGBdT7v7u6Oj48P27dv19m+detWQkJCmpQ8LdzHruVB2jUoLNFMjRkaaAooerdgfzErC805zUxb7pyCINy1xMiQ0CqmTZtGWFgY/v6aT+p79+7lzz//5JlnnsHBwQGAd955h02bNhEXFycd99JLL/Hqq6/i4eFBr1692Lt3L4cPH+bXX3+9I69DuIsoaiDjmqanWKUCLMw0nectTMGt4WKegiAIDRHBkNAqvL29WbduHVlZWahUKry8vHjnnXeYOHGitI9KpUKpVOocN2TIECorK/nxxx9ZvHgxnp6ezJs3TxRcfNCVlmsqSecWaur9WJiDTA2eXmBi0vTzqVRQXKpZIm9i3NJ3q6u0HJLTNdfycm2ZZf6CILQomVq7VEcQHiDa1WQNrTgT7hJZuZrqz+WVmgTpghLwdAYXJzBs5ue5tCxIugrGRtApoHXrBqVmQEqG5utgP7Czbr1r3UfEz6hwO4mRIUEQ7l5pWZrRoEqF5rFK/f91hG5F1f/OV1mlWZbfmp01rMxBX64ZgTJtxiiWIAitTgRDgiDcfYqKQanWLG0vLgVbK5DLwNFO03D1Vrk6agIUs/9VlG5N1pbQvYNmeq+5fdEEQWhVIhgSBOHukv2/1WLlFeDuAs52mhEhR9uWm2IyNQYvt5Y5V2MYiLdaQbibiZ9QQRDuHlcyNcnNpeWaxyXl0MHvzt6TIAj3PREMCYJw55WWQnoeqJWgb6AZBapSgLXZnb4zQRAeACIYEgThzsrM1iRIV1Roqj472WraYfh5gHkzix5m5GiatDrZ3XzfxiyzLy3TTNVZmjfvfgRBuKuJYEgQhDsnvxCuZGmCIW1PMSMjTT0e42bW/0lJ1/Qr05NpAhiXm3SaT89ueJl9YQnExINaDR3aapK5BUG4r4hgSBCEOyPpKhSVgLmZJhiqUYK3m6YNxq3QNllVqTW9y266//+63de3zF5RrQmE4P+X5KtUml5ogiDcF0QwJAjCbRUTE0NhYSG9Da2RVSnAUKEZvTE1vvX6QaA5l1qtCVZuNioE4OoE+vr1L7O3swJfd01wZW+j6Y2WdFUzBeftBjLZrd+zIAh3lAiGBEG4rWJiYkhJSSFgUAROMhlYW4C/V/NPmFeoadjqaKOZ4rI0b1puz82W2cvl0Oa63mfZ+ZrRorQsTb2i4lKortbUQBJL6AXhniR+cgVBuC0OHDhAfn4+VVVVKJVK1kb9w1NjxmJj34gk5/qUVsD5RM1IUE01eLdpuRuuj5MtlFVo6h9VVMCFJM12NbpBkyAI9wwRDAmC0KpKS0spLi4mKiqKyspKgoKCsLW1xd7eHhvnZgYPimpNknSVQtPuorCk4erO5ZWQV6DJT7KxbN41tRztwMFWMz1WXKr5W60W1aUF4R4mgiFBEFpNbGwsp06dori4mMDAQKKjowEYNWpU809aWgZp2ZpK1aAZjXFzbDjIScvSNHzV04PuQZoVa7dCmydkaa5ZgVZdU/f11WrIKdA872gDBqJjvSDcjUQwJAhCq0hMTKSgoIDU1FQAXF1dGTRoEPb2jUhqrk9eIWTmaEaETIxAUaNZ6n6z0R5tLo+hQcuvAmsoP6mo5LppNFXLJIgLgtDiRDAkCEKL+/vvvzl27Bje3t60b9+ea9eu4eTkRFhYWPNOqFZrWnWkZoKDtWabqTG0dwWLRlSpdncGSzNN1/jbOTojl183jaYPJWWa1WhW5pqpNkEQ7goiGBIEocWUl5ejVqu5du0aSqWSy5cvM2bMGAYNGoSVVTOLFdYoNYFQcZkmqMguAE8XcHGoXSAR/r8m0PVL3g30m9/tvqZGU9FardZc07AJwZSFGXQM0JzDxhIupWhWo2XkaJ4zvsXpOkEQWoQIhgRBaBFRUVGcOXMGPT09goKCqKysxMHBAVtb2+YHQsWlkHhVE0xYmoNKqRlV8XCpe7qrohLiUzVFEf09wayZ7Tyul1cEyemarw0NNAFRU1hdN41m+r+q2hamoN/IhOsqhSbfydhIU6W7MXWNtEv/a5Tg4Vx/mxFBEAARDAmC0EKuXbtGVlYWAM7OzkybNu3WTlhYohkRMtDXLGWvrtGMCNk1MMJTVKo5Tnt8SwRDxkaa1h5q6h6Jagp3Z7C21OQ76Tfy7TczF1IzNF+bGDWuhlJRCVy9pvna1FhzXUEQ6iWCIUEQmi0uLo6EhAQA3NzcyMjIQCaT4ex8C798VSrNqEZphaaYYWkFONhoRkUaCoRAMwpjbQFKFVhZNP8ebjxnaKBmmqy5jWO19PR0R4oaw/B/b9NyeeNHk0xNNIFbTY1mFEoQhAaJYEgQhGZLTk7mzJkzABgYGDBu3DiMjY0xNb2FX8D5RZDyv5EQawuws9Z0sK8rV0elgqtZUFapWV5vaQ4h/prnWqpNRlmFZhWbZSMStVuDs71mmstQXxPkNIaZCXRpr2khcqujWYLwABDBkCAITZaUlISJiQkWFhbo/S93x9zcHFvb5q+QKi0tRalUYmVooJkaq/7fqIana90FDatr4EoGXM3WPDbQ1wRDLd0rLDVDUytILoceHW5/yw09veYVihQ1jQSh0UTbZUG4A+bMmcMLL7wAwMSJE/n0009r7fP3338TEBAgPd6wYQMBAQG1cnGKi4sJCAggKipK2hYQECD9CQwMpF+/fsydOxdFY7q438Tu3bv5448/+Pvvv3F1deXRRx9l0KBB9OnTp9nnTElJ4bfffuPnn3/mfFoqBPpCgJemZ1h9lZ3LKyG/+P+TkpvSj6wptEGFkSGInqyCcF8SI0OCcA/R19fn2LFjHDt27KY1e+bOnUvv3r2pqanh4sWLvP3225iYmPDKK6/c0j1ol80nJSXRpUsXevTocUvnu3TpEhcuXMDMzEwq0hgUFATcJOfH1FiTIF2lgGA/zXRaa/B0ARsLzdRTY5OeBUG4p4ifbEG4h5iYmDBkyBC+/vpr1q5d2+C+lpaWODholoG7uLjQv39/4uLimnXdixcvIpPJCAgIwNPTk6qqKpydnTG6hbYWpaWlXL16lb1795Kbm0vbtm3x8fGhffv2jTuBgT6099YkNrd0VenrGRo0v0aRIAj3BBEMCcI9Zvbs2Tz66KPs3LmTwYMHN+qY5ORkoqKimtUTLDIykkOHDmFubk5paSl9+vS5pSkxrV27dnHu3Dnat29PeXk5rq6u9OvXr859VSoVFRUVmJndkMQsk7V8jpAgCA8cEQwJrWLHjh1s2bKF8+fPU1RUhLu7OxMmTOCJJ56QEm7rMnHiRI4fP15r+/bt2/H19W3NW75nODk58cwzzzBv3jweeeSRevd77bXXkMvl1NTUoFAoePjhh5kxY0aTr5eTk4NSqaSoqIiCgoJbuXUAYmJiyM/PJy0tDYCrV68yduxYXF1d69xfqVSya9cuoqOjGTJkCF26dLnlexAEQbieCIaEVrFkyRJcXV158803sbOzIyoqik8//ZS0tDTeeuutBo8NDQ2ttU+bNm1a83bvOc8++yxr1qxh/fr1DBkypM593n77bXr16oVSqeTKlSvMnTuXN998k3nz5jXpWu7u7lRXV2NkZISnp+ct3/upU6e4cuUKISEh0oiQl5dXnfsWFxcTFRXFyZMnUavVXLhwQQRDgiC0OBEMCa3ixx9/1FlmHRYWRnl5OStXruTVV1/F0LD+2ieWlpZ06tTpNtzl3cHMzIzS0tJa24uLizE3r3uFlKWlJc899xzff/99vVNLDg4OUvDi4+NDWVkZr732Gq+88kqDQU1kZCQZGRm4ubnRp08fevTocctJ0gAHDhwgJycH/f8lIWdkZPDUU09hbW1d7zFpaWmcOHGCgIAASktL6dq1a+MuVlquaYhqbASuDmIqTRCEBoml9UKrqKveTPv27amqqqKwsPD239BdzMfHh3PnztXaHhsbi7e3d73HTZw4ET09PZYtW9ao62inJysrK+vdJycnh5MnTxIfH8/Zs2cb3LcpcnJyiIqKIi4uDgMDA8LCwggPD683EEpJSeH06dPY29vj5ORETk4OQ4cOpV27dpodapSQkq5pfFp2wz0Wl0JcIhQUQ1aOJjC62ymqNX3VBEG4I8TIkHDbnDp1Cmtra+zs7Brc7/jx43Tq1AmlUknHjh15+eWX6datW5OvN2DAgHqfy8zMxMXFpcnnbA1PPvkkK1eu5MMPP2T8+PEYGRlx5MgR1q1bxxdffFHvcUZGRrz44ot89NFHdT5fXFxMTk4OKpWK1NRUFi5ciJeXl07uVXx8PImJifj5+dG2bVsMDQ1xcnKitLQUR0dHjI1vrcFnRkYGUVFRlJeX07NnT/bv34++vj6DBg2qc3+1Wk1qaiorVqxAqVTy8MMPM2nSJNRqNQbXFxEsLoXUzP99IwzB7Lp8o8JSqKjSfG1n3bQu83dCVTWcS9AEbe28wanhnw9BEFqeCIaE2yI2NpYNGzYwa9Ys5PUV0QO6devGiBEj8PLyIjs7m8WLFzNlyhSWL19O586db+Mdty6VSiVNF7Vp04aVK1cyb948pk6dSlVVFV5eXnz++ef15gNpjRo1iiVLlnD58uVaz7399tsAyGQy7O3t6datG6+99hr6+vrk5+fz9NNPs2PHDmn/IUOGsHLlSrp3707btm2xt7e/5dd56dIlYmJiADA0NGTYsGENjnZFR0cTGxuL7H/TWjKZTPo+AeTm5nL06FG8XdwIMjFCVqkAixtWmNlYQp65po+Xl+vd346iqur/R69Ky0UwJAh3gEytVqvv9E0I97ecnBzGjRuHk5MTy5cv1/2EfxPl5eVERETg6+vLL7/80mL3pB012rt3b4udsymmTZuGp6cn77///h25/tChQ4mMjGTw4MF4enqSmprKrl276NOnD9u3b7/l8x85coTU1FTatGnDmTNnKCoqIjw8vN78Jq3Nmzdz+vRpfHx8CAgIICQkRBqdSk9P5/jx41JwNfWZZ3B3cUVtZMjJkyfJy8sjNDQUR0dHTe2heyVPSKWC9GxNRW1XR9FY9X/u9M+o8GARI0NCqyopKeHZZ5/F2NiYRYsWNSkQAjA1NaVv377s2rWrle7w9ioqKuL06dMcP36cCRMm3JF7iI+PZ8eOHYwePZqQkBAAQkJCUKvVbNy4kYSEBNq2bXtL10hNTSU+Pp74+HjGjBmDgYEB/v7+de5bVlZGcXExjo6OdO7cGbVajaurK127dpVGiEAzfVpeXo5cLsfKygozKyswNiIzI0MK4GQymWYK7l4JhEBTMNLd+U7fhSA80EQwJLSaqqoqZs6cSW5uLmvWrMHGpnlVfO+nwct33nmH2NhYpk6d2mBOU2tKTEwEqLWiTLu8/fLly80KhvLy8oiJiUEmk0l5Yfb29ujr69cbCFVVVbF27VpSU1N55JFHeOihh3B3d9fZJzk5merqapydndm9ezehoaH06dMHKysrQNMg1tHRkezsbKnito7KKki/pulx1sZJtNQQ7ogFCxbw/fff19ru7e3Nzp07dWqsyeVyLCws8Pb2pnfv3jz55JO13j+v71toYGCAi4sLffv2Zfbs2Q2u0GysmJgYPvvsM+Li4rC2tmbcuHG88MILDdaJ01q8eDErV64kJycHf39/3nzzTZ0VqVevXq3z/a9jx478+eeft3zvzSHeFYRWUVNTw8svv8zFixdZsWIFbm5uzTpPeXk5kZGRdOjQoYXv8M744Ycf7vQtSAnUqamp0sgQaFZwAfj5+TXrvKdPn+bw4cMA9O7dm0GDBmFhYaHzpn29uLg4rl27xpUrVwDIzs7WeV6tVhMfH8+uXbsoKChg5MiRPPfcc1hZWWFq+v9TSZaWljz99NOUl5drpshulFP4/53tzUzAofZKR0G4HYyNjVm6dGmtbVraGmsqlUoaRV62bBmrVq3i119//f/VlP8zceJEIiIiUCgUHD9+nB9//JGUlBR+/fXXW7rPtLQ0Jk+eTPfu3fnpp59ITEzkyy+/pLq6mldffbXBYxcvXsy8efN49dVXCQwMZO3atTz77LOsXbu21nvBa6+9phMk1aowfxuJYEhoFR999BH79+/njTfeoLKykjNnzkjP+fn5YW5uzjvvvMOmTZukflknT55k8eLFDBw4EFdXV7Kzs1myZAk5OTl8++23d+iV3H/8/f0ZMmQIu3btQq1W4+XlRUpKCrt372bIkCHNniKrqamRvlYqlQ02klWpVERGRpKbm0tQUBDGxsa1akudOnWKbdu24ejoiI2NDUqlst4VgBYWFlhY1NPY1cxYM22mLweTW1sdJwi3Qk9Pr8EaajfWWHv44Yd54oknGDduHK+88grbt2/XGZlxcXGR9u/evTvZ2dmsWbOG7Ozsuj8Y1KO0tBSFQiGVRPn111+xtLTku+++w9DQkJ49e1JaWsrChQuZNm0alpaWdZ5HoVCwaNEinnnmGaZNmybd17Bhw/jxxx9rFXz19PS8a2rKiWBIaBX//PMPAF9++WWt55YtW0aPHj1QqVQolUppu4ODAwqFgm+++YbCwkJMTEzo3LkzH374oc4IhtA0J0+eJCEhAblcjr+/P506dWLlypU89dRTbNy4UdpPu5qsKc6cOcOlS5cAzbB99+7dkclkDa4Yi4yMJDU1FT8/P/Ly8igsLGTKlCnSm3xNTQ1HjhwhPT0d0IwYDR8+/H+d7JvB1gq6Bmlyc4zv8pVlgnADV1dXZs6cyUcffcSRI0cIDw+vd1/tyFFmZuZNgyG1Wk1UVBTr169n9+7dfP3111J7n4MHD/LII4/oFMcdNmwY8+bN4+jRo/WWxoiOjqakpISIiAhpm1wuZ+jQofz222+o1WqdPMC7iQiGhFaxb9++m+7z+eef8/nnn0uPPT09Wbx4cWve1gPp6tWrxMfHA5r8mk6dOmFjY8P27dtJSEjg8uXLUp2hpkpLS+PixYuAJtl92LBhNz3m3Llz5ObmkpGRwejRo7G1tZUCoYqKCmJiYkhMTEQul9OuXTt8fX3p1KnTrb2JmooRIeHucP0IKmiChZv939YGQGfOnGkwGMrMzERPT6/BtIT09HQ2btzIxo0buXr1Kp07d+add96hZ8+egCY1ISMjo1YvSDc3N0xMTKScw7pon/Px8dHZ7uvrS1lZGdeuXcPZ+f8XC3zwwQe8+uqrWFtbM2DAAF5//fUWyXdqDhEMCcJ9zt7eHiMjI/T19WtVBm/btu0trRyzt7fHxMQE4KbFNHfu3ElycjIeHh7k5ubi5eWFv7+/Th2hEydOsH//fkxMTLC1taVr164EBgbWeb6qqir27dtHZmYmAwYMaH7ftCoFKFUiYBJaXXl5ea0Rzi+++IIRI0Y0eJx2ejgnJ0dnu0qlkhoxnzhxgtWrV/PUU0/VqhFWVVXF7t272bBhA0ePHsXZ2ZkRI0YwatSoWn0BS0pKAOqcCrO0tKSoqKje+ywuLsbQ0LBWsVbtYofCwkKcnZ0xNDRkwoQJhIeHY2lpydmzZ/nxxx85d+4ca9eubfKq45YggiFBuM+Fh4fj5OSEWq2ud1VXU0RGRnLp0iVcXFwIDg5mxIgRyOXyBhOv8/LyOH36NAqFAn19fSZOnCitNAPNJ8pjx45RXV1NUFAQ8fHxPPbYY/XmCJWXl3PkyBFp9c2lS5eaFwyVV0JsgiYgCvQB++ateBSExjA2NmbFihU6225cPVkX7YraG0eQvvrqK7766ivpcZcuXZgzZ47OPhcvXuTpp5+mpqaGgQMH8ttvvxEWFnbTVWF1jVY1ZpqrvuOuf87R0ZEPPvhAel5b6HXGjBns2bOHoUOHNniN1iCCIUF4ANxq3aDrXblyhczMTDIzM/H29iY4OLjefXNzczl06BCVlZV07tyZ06dP4+7urjOMfu3aNS5fvixV0Q4JCeHJJ59ssF1Keno6Fy5cwNXVlcLCQuzt7Tl16hTt2rVr2oqUyirNH4DSChEMCa1KT0+vWStjs7KyAGqN+DzzzDMMHz6ciooKNm/ezNq1a/n222/517/+Je2jr6+PmZkZubm5lJSUUFJSQk1NTb3NsrUjQnWNAJWUlNSbPK09tqqqiqqqKoyMjKTtxcXFwP+PENWlb9++mJqacv78eREMCYJw93N2dubKlSt4eXlhbm7e4L5xcXFSxeigoCBmzJihM1VXVFTE2rVrMTIyws7OjqqqKtzc3PDy8iIhIYF9+/bh7+9Pnz59kMvlFBUVER0djZmZGWZmZlRUVDB8+HDWrl2LUqmkpKTkplWudViZg5cbKBTgKAIh4e6kXZASGhqqs93Z2VkKrrp3705+fj5LlizR+TDh5+fH/v37+eeff1i/fj2vv/46pqamDB06lFGjRtVanGJiYoKrq2ut3KD09HQqKipq5RJdT/tcYmKizvR2YmIiZmZmODk5NfM70PpEMCQI97iYmBhSU1OxsrKiT58+LX7+uLg4kpOTMTExoX///gwcOBA/Pz9MTEx0kiGvFx0dzdWrV3FwcMDGxobi4mIcHBxq5SyVl5dTUFCASqWic+fO9OzZEwcHB5KSkoiLi0OhUHDw4EE6dOiAvb09sbGxHDx4EICnn34aV1dXysvL0dPTQ6lUNqognA65HDzvjoa9glCXjIwMFi5ciK+vb4PlKgBef/119u/fz+LFi3n33Xel7Xp6evTp04c+ffpQWFjIli1bWL9+PX/88Qc+Pj6MGjWKcePGScnLffr0Ye/evbz55pvSCNK2bdswMjKSEq3rEhoaioWFBdu3b5eCIaVSyY4dO+jbt2+DU2z79++nvLz8jtWUE8GQINzjLl++TGxsLHp6epiYmNCtW7cWP//p06cBMDIy4qGHHmpw6TxoPgnGxcVhYGDAiBEjMDU1rfMYFxcXHnnkETIyMggICMDBwYGcnBxWrlyJSqXCz88PT09PaXhdW4XXzMyMqqoqkpOTadu2Lc888wwFBQU3nQ5MT08nKioKBwcHevbsqZO8LQh3WnFxMWfOnEGtVktFF1evXo2BgQHz58+/abDv4+PD0KFDWbduHbNmzaqz6r+1tTUTJ05k4sSJxMXFsX79ehYvXoyPj4+0tH769Ols2bKFV155hYkTJ5KUlMTChQuZMmWKzjTZpEmTyMjIYM+ePYCmGfPMmTOZN28etra2UtHFtLQ0vvnmG+m4//73v8hkMjp27IilpSUxMTH89NNPBAcHS/dwu4l3AkG4x8nlckDz6U/7dUvSvgHLZLJGj7xoPwHK5XLUarVOIHTy5ElSU1NxdXWlZ8+etT5paq+jUqlwd3end+/e0vmCgoKwtbWltLSUVatWoVareeyxx+jatStt2rQBoKCggMOHD2NkZER4eLi02g0gNjaW2NhYQPOLo7mV0VtcpQIM5JqRKqF11dRAjQr09e661izR0dGMHz9epx3HpEmTmDBhQqPbGc2aNYsdO3awYsUKXnzxxQb3DQwMJDAwkLfeeovKykppu7u7O0uWLGHu3Lk899xzWFtbM23aNF544QWd42+sFQcwdepU1Go1y5cvJzc3F39/f37++Wed6tM+Pj6sWrWKNWvWUFlZiZOTE2PGjOGll166Yx9QRNd64YF0P3XEjouL48qVK1hYWPDQQw+1+PkTEhJISkrC1NSU3r1717vfyZMniY2NRSaT0aFDB7KysrC1ta0V7Pzyyy9kZGRgYWHB5MmTpamzq1evUl1djZeXF1evXqWwsBBXV1cOHDhAZWUljz76qNR77MqVKyxZsgSAQYMG6UwfHDlyRPqkOm7cONq3by89d/78eTZs2ECbNm0YN27cHS3/L8nMgfhUTXHI9j6aStlCy/+MVirgWp7m+12lACNDcHEAJztRjFMQI0MNCQgIwMTEhJdffpkpU6YAkJ+fz5w5czh+/DhOTk68//77rfILCOCPP/5g7dq1xMfH8/zzz9eK8idOnMiZM2ekSLpDhw4sW7asUfc5fPhwkpKSGDFiBJ9++mmr3L9we2g/3bWUY8eOkZWVhYuLCz169Gh0LaKMjAypz5idnV2tAoynTp0iIyMDZ2dnMjIyMDMzk1acXLlyhd9//x21Ws2YMWMICgrCysqKU6dOce7cOUDzaVIbDHl4ePDEE09QVlYmvXbtp1QXFxcMDAwwMzOrtfomKCgId3d3jIyMdFa73FFFpZq/84s0idz6Jg3vLzRdpQIuJEJx2f9vq1JASjrkF0J7XxEQPeBEMFQPbZXQnTt36iSJfvjhh9jb23P06FGOHDnCK6+8wu7du5vckX3OnDl0796d0aNH17uPo6MjL774Ips2bap3n08++aTOgl03u8/NmzezYMECacmmIIBmmXt0dDQ5OTnk5OQQFBR00xVj+fn5AFKytPbrG/f5559/KCwsxNPTk379+uHi4iKNzFRWVkq1SLRfnz59moSEBOzt7VEqlcjlcpYsWYKbmxuPPPKIzrB7eXk5W7duJT09neHDhzN79mz09fV1GrpqNbQ0+I5wtgOVCizNRe+01nItTzcQul5xGWTngYdIpH+Q3ZPBkEqlYunSpaxevZr8/Hz69+/Pxx9/jKGhIR9++CFVVVV89tlnqFQqZs2ahZubG++++y6rV69m586d6OvrExMTg6OjI/Pnz8fPz4+lS5dy8uRJDA0N2bdvn06yl1ZZWRl79+5lz549mJiYMGDAANq1a8fevXsZM2ZMi79ObSJZU4eJb/d9CvcPlUol5efIZLKbBkJRUVFScnXnzp0ZMWIEBgYGuLq6SvucO3cOpVIpjcTIZDL69u2rcx5fX1+GDx9OTU0Nbdu2ZdOmTaSmpuLg4EBJSQlPPvkk27Zt48qVK1y5coWgoCCdfJ/c3FwuXLgAQFJSUq3lv/n5+ejr6999gRCAtaXmj9A6amogM7vhfTJywNVRTFE+wJq4DvXu8O2337J3716WLVvGgQMHyMrKYu3atQDMmDGDHTt2kJGRwVdffYVKpeLtt98GNLkPsbGxTJo0icOHDxMSEsL8+fMBTQXb48ePM27cOE6dOlVn/5fU1FRMTU11isH5+/tLxeLuhLlz5xIWFsakSZOkXwZ3430K9wYXFxe6du1Kly5d6Nix4033v3btmvQnOzsbT09PnUDo1KlT7N69m7/++gt/f3+6du1K9+7dAU0gtWbNGo4dO4ZcLqdz586EhISQlJRETEwMRUVFmJmZMXz4cGxsbGjTpg0ymQwfH59aS/QdHR0JDQ3FxcWlVpXtxMREFi5cyM8//8y1a9da4Lsk3FNqVFBV3fA+VQq4IRFYeLDccyND2dnZLFu2jJ07d0oFnCIiIoiOjgY0RahGjhzJzJkzAU3ejXaFTXx8PDNnzpSSQIcNGybly1y6dIlZs2bRo0cPgDpXzZSXl9f6pGxubk5BQUErvNKbe+ONN/D19UUul7Nq1SqmT5/Ozp0777r7FO4tTVma7+TkJAU/ddUc0la8BU1LjrFjxwKgUCg4fvw4+fn5ZGZm0qlTJ4yNjTl69ChnzpzB29ub4uJiQkJCpPP369ePwMBALC0ta/U+MjY2rrdJbHZ2NkqlkrKyMvLy8nQKv5WVlbFnzx4KCgp49NFH757VZULL0dcDI4OGAyIjQ7GS7wF3zwVDR44cQaFQ8Nhjj0nblEql9CYL0L59e/744w9Wr16ts1rk8uXLfPbZZ9Lj/Px8bGxsUKlUJCYmMmjQoAavbWpqSmlpqc620tLSOvMS6jJjxgxOnToFaPIiduzYId3Pc889x3PPPdeo82hdXzl0ypQprF+/nujoaBwcHG7pPoU7b//+/RQUFODh4UHXrl1b7ToHDhwgLy8Pd3d3acTmZqKiokhLS8PBwYG+fftK7Tiu/1k7fvw4aWlp2Nvb07lzZ8rLy6XeYUeOHCE7OxsHBwfy8/Oxs7OTgpuKigqKiopQKBQ8+eSTJCcno1QqpQRuR0dHQNPrKDY2lrKyMkJCQhpcFRYYGEhxcTFGRka1ps8yMzM5e/YsoBk5FsHQfUhfH1wcNcnS9XF1aNUpstTUVBYvXszZs2dJSEjAx8eHrVu31trv8OHDbNiwgbNnz5KWlsZTTz3F+++/X2u/t956i9OnT5OdnY2BgQH+/v7MnDmzwY72/fv3Jz29ge8BMHv2bF588UUyMzP57rvviIqKIicnBysrK/z8/Bg1apROjuqZM2f4/vvvuXDhAiUlJdjb2xMcHMy0adMaNbJ8N2lWMFRSUkK3bt2YM2cOkydPbuFbalhRURHDhw9n7ty5dT4fExPD999/z+DBg9m4cSOdO3cGNJ9K8/PzdYbX9+zZQ+/evUlNTW1UqXBPT0/Ky8vJysqSPgXHx8fftOOw1k8//SR93ZgE6qbS5nrc6n0Kd1Z0dDSHDh1CrVZTU1PTasFQTEwMhw4dkjpfNzYYSkxMJCEhAX19fZycnGjXrl2tfZKTk7l48SJyuZzhw4frBO7nz58nIyMDNzc3hg0bhoeHh/Rcjx49sLCwwMXFhZiYGE6cOIFcLmf27NlSdVzQ/HLZuHEjoAmMevXqhVqt5vz581KAZGJiQk1NDXFxcVKBtxtXkDk6OuLj40NeXt5NC0kK9zAnO82qsbqSqC3NwNGuVS+fkJBAZGQkHTt2RKVSUV9Fm4MHD3LhwgW6devWYHf4mpoapk2bhoeHB5WVlaxbt47nnnuOZcuW1ft+8f3336NQKKTHs2fPJjQ0lKlTp0rbnJ2dKSoqYuzYsVhbW/Piiy/i6upKVlYWx44d49ChQ9LvkZMnTzJp0iR69+7Nhx9+iJmZGampqfz999/ExMQ8GMHQuXPnUKvVDTZobC1BQUH88ssvJCYm4uvrS0FBAbGxsfTp04eMjAxeeuklvvzyS7y9vRk8eDAzZszAzc2N+Ph45HI527dvZ+TIkWzatImYmBg+/vhjDh8+XOcb+o3MzMzo378/CxYs4L333uPo0aNcvHiRb7/9FkDqFvz555+3yGutqalBqVRKv6yqqqrQ19dHLpdTXFxMbGysNKWxevVqcnNz6dSp003vU7i7GRgYYGJiQnl5easu/5bJZJiYmFBWVtak62j3NTU1rbe8vraEv4mJiTRNffHiRa5du4aXlxcZGRkolUq8vb3Jysri9OnTdOjQAWdnZ7p168bOnTulInAWFhY6hdiqq6sxNjZGX1+fmpoaacQzNTWV9evXY2dnR3Z2Nvb29jg5ObF7927pvm9M3La0tOTJJ59EqVTW27hSuA8YG2qWz2fnaZKltXWGXB00gVArL6vv37+/tCBmzpw5UrmIG7311ltSjmtUVFS95/v66691Hvfp04cBAwbw119/1RsM3Vh+w9DQEHt7ezp16qSz/c8//yQnJ4c///xTJ/9vxIgRqFQq6fGqVatwc3Pjhx9+kH7Ge/bsyRNPPKGz372iWcFQbGwscrm8RWubNFbXrl2ZPHkyU6dOpbi4GDs7O8aPH09oaCgzZszQyfsZPnw4ixYt4pNPPiE+Pp7HH3+cbdu2MXfuXIKCgvjtt9+wsLAgPj6+VtJlfT744APeeustevTogZOTk1R2HDSdhVuy2+6iRYv4/vvvpcc//vgjc+fOZfTo0dTU1PD111+TnJyMgYEBAQEB/Pzzz1LbgobuU7i7dejQgYqKCoqLi/Hy8mrV61RWVlJUVIS7u3ujjwsKCsLS0hIbGxud5e0XLlzg0qVLyGQyAgICMDc3x9ramqCgIKkq9NWrV2nXrh39+vXD2toaPT091q1bh0qloqysjMGDB3P+/HlUKhWZmZn06tWL0NBQKQfuypUr/PXXX9jY2PDUU0+hUqmk75GhoSFyuRxLS0sph3DkyJFYWlpSUlKCqakp+/fvp3379jr5TXK5vFUqdwt3GWNDzfJ5VwdQqjQ5Qrdp9VhjK7c3ubfe/2grVmtLwtyK4uJi9PT0sLOrPVp2/f2VlJRga2tb589Oc1/HndTskSFfX1+dHJTt27ezfPlyLl26hLGxMWFhYbz11ls6U09qtZqVK1fyxx9/kJaWhqenJ2+88QabN2/m4sWLbNu2rVHXnz59OtOnT6+1fcuWLTqPP/jgA+nrhIQEgoOD+fjjj2sd99JLLzXqugC2trb88ssvtbbX1NSQnZ3NqFGjGnWexowevfjii/WWU7e1tWXDhg1Nvk/h3tDYKatb1Zhk6TNnzpCSkoKpqSldunShXbt2dY6kJiYmSvk3hoaGDBkyRHquoqJCqkdUVFTE+PHjiY6O5vDhwzg4OHDt2jXs7OzYt28fJ06cwN7enrZt2+Ln56eTD5SSkkJ+fj75+flSQUgtV1dXpkyZQnp6OikpKejr6+Po6Mi0adMoLCxk7dq1lJaWkp2dzfjx4xv1/UlISODatWsEBQU1uZaYcJfS178Hs2VrU6vVKJVKSkpK2LBhA6mpqXz00Ue3fN6goCBUKhWvv/46U6dOpUOHDnW2yAgKCmLhwoXMnz+fYcOGNdjN/l7Q7GBIO/oC8PHHH7NmzRqmTJnCSy+9RF5eHvPnz2fq1Kls2LBBGlb/z3/+w4YNG5g8eTJhYWGkpqYyZ84cDAwM6NWrV8u8onokJCQwfPjwJh1jaGhIREQEs2fPvmlulL6+Ptu3b7+FO7y9Ro0aRUpKSpO/J8KDJzk5mZiYGEAz7VVfSw4LCwvpE6GFhQWgSdyPjIykvLycHj16kJmZiZubG0qlkqNHj5Kbm4uPjw8TJ06kpKSE4uJi5HI5ubm5tG/fnjVr1tCmTRsGDx6MsbExvr6+XL58GSsrK50hfC03Nzfc3Nxwd3fHwMBAqkCtnW4GzcrKqKgofH19a1Wovl5+fj6rV6+WRq1utsBCEG6ndevWSZ3pTU1NmTdvnpQjeyt69uzJtGnTWLJkCbt378bY2JguXbowfPhwRowYIU2NT5s2jbNnz7Jo0SIWLVqEtbU14eHhTJgwoVUXfbSWJgdD+fn5pKen06FDBwDWr1/PihUr+OGHH3S6zVpYWPDcc89x7Ngx+vbty86dO1mzZg3//e9/GTlyJADh4eEUFBSwYMECKf9IoVDwn//8hyNHjlBSUoKfnx9z5swhNDT0ll7o5cuX8fHxadIx2oaO9yNt8qnwYIiKikIulzfrTUq70ktfX7/OvJoTJ04A0LdvX2lf7Yel6OhoTp48CWiGzsePH09iYiL//PMPnTp14u+//0ahUFBQUMDOnTtRKpXStJh2RWRiYiJJSUns2rWLIUOG6CR81uf6Glug6Xb/2GOPkZeXx+nTpzl58iT+/v5MmDCh3nPo6+tjZmZGSUmJTrNXQbgbaIvpFhQUsGPHDl555RW+//77WnlxzfHmm28yYcIE9u7dy6lTpzh69CiHDx/m8OHDfPnll4DmQ8Vvv/1GTEwMBw4c4NSpU+zatYtt27bx8ccf66zwvhc0ORjSBgja4OXnn3+me/fuOoEQIC2jzcjIADT5LqGhoVIgpKWd79cGVzU1Nbi5ubFq1SqcnZ3566+/mDlzJgcOHLilNyTtknZBeNBERkYSGRmJXC5HoVA0eRQ2JCQEY2NjTE1NdUaEAQ4dOsSBAwcAqKqqqrW018LCAhMTEyoqKqTRohMnTnDp0iXc3d0ZOXIkpqamZGVlSQnRRkZGnD17lsLCQoKDg9HT0yM3NxcjIyMuXrxI165ddZbWa/epa3l9TEwMycnJdOzYkcDAQKqrq4mLiwO4adK4paUlEydOpKCgoFVztwShOWxtbaU80D59+lBQUMCXX37ZIsEQaDrXT548mcmTJ1NWVsbLL7/M5s2bmTZtms40eUhIiLRaNC0tjYkTJ/Lll1/e/8HQuXPnMDAwoF27dmRkZJCSklLnp6vMzExAs1QvJyeHCxcu8M4779S5n76+vvTNNTU1Zfbs2dLzo0aNYu7cuaSmpjZqxZcgCLqKioqkZfrFxcVNPl479VSX4uJiafrp+qXAR44cITU1FVtbWwYNGkRlZaU0hK/dT1tjaNu2bWRlZdGlSxfUajXm5uYUFhYCmmm52NhYKisrCQsLo7CwkMjISDw9Pdm4cSPu7u5SXk+/fv10cqBKSkr466+/UKlUVFRU4OXlhYGBAWPGjCEjI0P6wAaagqplZWXY29vrrJBzcHCo1WdNEO5GQUFBHD58uFXObWZmxpNPPsmhQ4dISkqq93exu7s7gwcPZsmSJeTm5jY4DX23aVYwFBAQgKGhIXl5eUDtpoygqZdgZGRE165dSUlJqXe/w4cP4+/vX++ntMTERCorK6XVLtevXhFa1qVLl+70LQitwNfXl5qaGuRyeaNq6Rw8eFCqA1RffpCWj48P1dWayr7Xnzs1NZX4+HhAs6qzR48eREZGkpmZSVBQENbW1ri4uKCnpye1yCgqKsLCwkJa8WViYoJKpSIoKIizZ8+Sl5dHQkICly5dYsKECejr62NnZ8eZM2cATW7T9cGQsbEx/v7+XLx4UWe1nJ2dnbRS5sqVKyQnJxMfH09GRgYRERF06dKlEd9VQbi7REdHN2lVaH20xYhvLJuh/T2uDXDqC3ZSUlIwNDS8O/sANqBZ02QDBgwAkD4tJicn6+yTlJTEypUrGTduHBYWFtIbT2Jios5+kZGRHD16lHHjxtV5rYqKCt58801mzpwpDYHfiV/YAQEBmJiY8PLLLzNlypRGH/fHH3+wdu1a4uPjef7552utDJs4cSJnzpyRMvU7dOjAsmXLAM1/yDlz5nD8+HGcnJx4//33eeihh256zYaOGz58OElJSYwYMUJqQyLc/4KCgggKCmrUvteuXePUqVMUFxeTl5dH165da01Pp6SkcOXKFaysrOjYsSPt27evdR5tgUQHBwdMTU25du0ax48fp7y8nOLiYp577jn279/Pjh076NmzJ/n5+fj4+JCamkp1dbVU7uLChQvIZDKGDRtGdnY2CQkJuLi4UFxczOOPP058fDwBAQHk5+fXKo9hYGDAyJEjpRIcdTl48CC2trbSdH5WVlajvk+C0BQVFRVERkYCkJ6eTmlpKTt37gQ0K0e1013p6elSKkpFRQVXrlyR9hs8eDCgqRq/adMm+vXrh4uLC0VFRWzevJkjR47U2WC8qTZu3Mhff/3FiBEjCAwMRK1WEx0dzS+//EJQUJD0YeHdd99FqVTy6KOP4uXlRWlpKbt372b//v1MmjTpnqvb1aRgKDs7m5ycHCm/x9bWlkcffZQlS5ZgY2ND27ZtuXDhAj/++CMdO3bk9ddfBzTJjCEhISxZsgRbW1v8/PyIjo6WmqteX51Wq7q6mldeeQU/Pz+ef/75W32dzaat27Bz5846ey81xNHRkRdffJFNmzbVu88nn3xSZ2XoDz/8EHt7e44ePcqRI0d45ZVX2L17902X9zZ03ObNm1mwYIF4wxfqZWpqio2NDcXFxVhbW9eZp3f27FnOnDmDnZ0dpqamOsvbDx06hEwmIywsDAcHB4yNjQkICJBqkpSXl2NlZYVCoeDs2bMUFRVRWFjI0KFD2bhxI3Z2doSGhmJsbExZmaZasI2NDS4uLnTo0AFTU1POnDnD1q1bGTt2LImJiSgUCoYNGybVPbty5QoqlQpPT0+MjIwanOZydnbmxIkTBAQEoKenV2s1zpUrV8jJyZHqJglCc+Tl5fHyyy/rbNM+XrZsmZSLFxUVJRVdBM3P06FDh4D/Hwhwd3dHoVDw9ddfU1BQINX7Wr58eYuU5Ojbty8ZGRls2rSJhQsXolKpcHV1ZerUqUyZMkWqK/TUU0+xadMmfvrpJ3JycjA2NsbDw4NPP/200SVm7iZNCoZuTJ4GTdf0efPm8csvv5Cfn4+7uztTpkxhypQpGBgYAJpKt/PmzeODDz7gq6++wtjYmH79+jFr1izeeecdwsLCdK6jUql466230NPT49NPP623yq1KpWLp0qWsXr2a/Px8+vfvz8cff4yhoSEffvghVVVVfPbZZ6hUKmbNmoWbmxvvvvsuq1evZufOnejr6xMTE4OjoyPz58/Hz8+PpUuXcvLkSQwNDdm3b98tRdrapPK9e/c26biysjL27t3Lnj17MDExkVYN7N27lzFjxrT4ca0lOTmZTz75hFOnTmFiYsJjjz3G66+/XqvJZl02btzITz/9RHp6Op6ensyaNUunbo3QOiwsLOjWrRs+Pj71BhHaVV4FBQUor+v0vW/fPumNu7q6mocffpj09HS2bNlCeXk5HTp0ICAgAGdnZ6KioggKCuLYsWP4+flRUVFBdXU1WVlZtG3blkOHDkkJ29cXSbS2tiY/Px8jIyPs7e2ZMmUKpaWl0ih1UlISK1asQK1WM378+AbzDKuqqnB3dycmJobMzEx69+6ts1y/oKCAFStWUF1dTUFBQa1FIvc6tVpd73ur0LLatGnTqFmN0aNH37RFk6+vLwsXLrzle9q3b1+d2/38/Hjvvfduenzv3r1vOo1+L2lSMDRgwIBa/6Dm5ua89957N/3mtWnThl9//VV6XFlZyeTJkwkPD681z/n++++Tk5PDr7/+WmexJ61vv/2WU6dOsWzZMszNzXnhhRdYu3YtTz31FDNmzGDIkCHMnj2bFStWoFKppIg7ISGB2NhY5s+fT1hYGP/5z3+YP38+33//PZcuXeL48eN89913fPnllzpv9q1h7ty5zJ07l4CAAObMmUP79u1JTU3F1NRUZ3mwv78/ly9fbvBczT2uNRQXFzNp0iRcXV357rvvyM/PZ+7cuRQWFvLVV181eOzOnTuZM2cOzz33HA899BB///03r776KhYWFg02IhRaxs2m1Ly9vdHX18fBwUEn2KiqqpK+1vZASkhIkKpB6+npMXbsWFatWkV8fDxubm5MmTKF6Oho/vnnH8LDwykuLsbS0hJbW1vy8/ORyWSUl5dTWlpKXl4e/v7+TJs2DWNjYylf4fqeZVVVVVLfp4qKinpfQ1VVFevWrePy5ct07dqVpKQkUlNT6dixo86HOG3dpHuxom59ampq2L9/PxcuXODRRx/V+TdUq9VcunSJ6upq2rdv3+D7ryDcT27L//TY2Fh27dpFaGgoZmZmpKSksGLFCgoKCli1apXOvunp6axduxYjIyOdEaNffvlFp0ZKdnY2y5YtY+fOnVKV64iICOmN19nZmZEjRzJz5kxAk7+jHd6Lj49n5syZUlQ7bNgwKYfm0qVLOi09WvNN8I033sDX1xe5XM6qVauYPn06O3fupLy8vNaQvLm5OQUFBQ2er7nHtYbVq1dTXFzMpk2bpPlwuVzO66+/zsyZMxusVvrtt98yePBg/vWvfwEQFhZGcnIy3333nQiG7gL1Lc1v27at9OFBuxTdysoKCwsLSktLpSnekpISAAoLC6murub06dOApgyHjY0N27Zto1OnTrRr146oqCjOnDlDaGgoR44cITw8XMpZrIuHhwe9evVCqVQ2WFesoqJC+pBQWFgoVbUODw+X3k+sra15+umnycvL05kKvNcVFRVx5MgRQNMv7vpgKDExkTVr1gCaXlQ39q0ShPvVbQmGysvLOXLkCKtWraKqqgpHR0f69OnDCy+8gKOjo86+bm5ujRpOPHLkCAqFgscee0zaplQqdWobtG/fnj/++IPVq1fr1CC5fPkyn332mfRYmz2vUqlITExsVKXZSZMmSYHXjaZNm8Yrr7xy03Ncnys1ZcoU1q9fT3R0NA4ODtJUhFZpaalO+5O6mJqaNuu41nDw4EF69uyp0w9t0KBBvPPOO0RGRtYbDKWlpZGUlMRrr72msz0iIoK3336b/Pz8u7LHWkxMDFlZWdjZ2d321UgpKSkkJiZiYWHR5JyBkydPUlBQgKenZ739+dLT04mPj6+zzhBoVoSq1WrCw8Px8/MDNB849uzZg7W1NQMHDqSmpgZ9fX12795Np06dpNVkSUlJdOnShfj4eDw9PVGr1ZiYmGBkZIRCocDExARnZ2f09fUxMTEhMzOT1NRUZDIZarUahUJBYWEhbm5ulJWVoVAopF/0Dg4O9f5bWFtbM3z4cNLS0rC1tSUrKwtHR8daq1rbtGlDmzZtmvQ9vdtZWVnRvXt3Lly4UGt17vXTZvfTaJgg3MxtCYZ69OjRYB+t5igqKmL48OHMnTu3zudjYmL4/vvvGTx4MBs3bpQSI/Py8mr9Qt2zZw+9e/cmNTUVMzMznX5q9Vm6dGnLvJDraN+IPD09KS8vJysrS8qViI+PrzPR+nrNPa41JCYm8vjjj+tsMzQ0xMPDo9aqwuslJSUB1PpU7+vri1qtJikpqdHBUEMjCJmZmbWqFN+K2NhYLl++jKOjI46Oji2yxLWxzp07x6lTpzAyMkJfX7/R1dpjY2M5cOAAZWVllJaW1hsMxcTEcPz4cWnK5PqA6MCBA9IqmZqaGvr16wfA+fPniYmJwczMjKFDh+Li4sL69evJysrCz8+Pp556iiVLlnDlyhXc3d0ZOHAgGzduRK1W079/fw4fPkxVVRVdu3YlOjqay5cv06NHD7Kysti4cSNGRka4uLhw8eJFqqqq8Pf3Jz4+nt69e6Ovr49KpdKZPqtL586d6dy5M9u3b8fY2Jj09HRpeu9+pq+vz5AhQxg4cGCtaTAfHx+efPJJampqGt28WhDuB/fshHBQUBC//PILiYmJ+Pr6UlBQQGxsLH369CEjI4OXXnqJL7/8Em9vbwYPHsyMGTNwc3MjPj4euVzO9u3bGTlyJJs2bSImJoaPP/6Yw4cPt2hhx5qaGqknUk1NDVVVVejr6yOXyykuLiY2Nlaqi7J69Wpyc3Pp1KkTZmZm9O/fnwULFvDee+9x9OhRLl68yLfffiude86cOYBuw9fGHHe7aHM/bmRpaalTnO9G2uduPNbKykrn+dvt4MGDHDx4UHr88ssvk5qaKq0U1E4PFRcX8/vvv0uB7dChQwkODuaLL76Qju3RowcDBw7ku+++k4og+vn58cQTT7By5UqpVIWNjQ2zZs1ix44dOhXU33nnHU6ePMnu3bsBpKKHVVVVbNu2TeqRN2bMGJydnfn++++lYx9++GEeeugh5s6dS01NjXSsQqHg559/Jjs7G9CMiEyePJn169dz/vx5QPP/WaFQcODAAf755x+da2u/R9rt2kTksrIy1q9fj0wmk3JxLl++zCeffCJ9z8rKytixY4eU6xMTEyMFJadOnZK2V1VVkZWVJT2Xk5MjPZeQkADAP//8w4QJEygsLNSZgh83bhz29vY6iacDBgygZ8+enD59GqVSiUwmY926dQwbNozt27eTk5MDaFbvTJo0iXXr1nHx4kVAMwr72muvsW/fPmkkCuBf//oX8fHxOk2jtX0Nf//9d2nbsGHD8Pf35+uvv5a29erVi/79+/PNN99QXl4OQLt27RgzZgxLly4lLS0N0Ix4zZgxg61bt0o1lvT09HjnnXc4evSozoKNF154gdzcXP78809p2/jx47G1tWXRokXStkceeYSwsDCdkhudO3fmscceY9GiRVJNOU9PTyZOnMiff/4p1ZEyNzdn9OjRbNmyRcrzAk0aQFxcnE4D7qlTp9bZU04Q7jSZWvtucg/69ddfWb58uVRHZPz48UyYMIEJEybwzDPPSFNmH3zwATU1NXzyyScsXbqUy5cvk5aWRkxMDEFBQXz88cd4eXnx3XffUVFRwVtvvaVznYCAACIjI5u8tH7BggU6v4hAkzA9evRo8vPzmT59OsnJyRgYGBAQEMCbb74plS3Iz8/nrbfe0qkXdH2+zOTJkxk6dGitGk03O067tL616wwFBQXx8ssv89xzz+lsf+KJJ3BwcGDBggV1Hrd582beeOMNDh8+rFPQKyUlhUGDBrFo0SL69+9/y/enHTVq6kq/+hw9epT09HScnJxu+wqL6OhoUlJSsLKyanA0rC4HDhwgLy8PLy+veqeUbuxaf33NnsuXL0sBQkBAgJRbc+LECa5cuYKdnR39+vWjuLhYmkp0c3OjoKAAa2trsrKysLKyIicnBycnJ8rLywkLC+PcuXPk5+ejVqulIKpt27ZcunRJCgDatm2LpaUlSqUSb29vSkpKCA4OlgLn8+fP888//9CxY0epSezvv/9OTU0N48eP15kiKikpYf78+ahUKgIDA++5VgJ32pYtW6S0geeff75Ro+s309I/o4LQkHt2ZAhg+vTpTJ8+vdb26z+VgSYY0kpISCA4OJiPP/641nEvvfRSi97fiy++WKvQopatrW2DU4e2trb88ssvdT5XU1NDdnZ2nbUcGjrudrK0tKyz9UNJSUmDydPXjwBdHwxpz3W3VjXt2bPnHbt2aGhosxsZa6e1GtKpU6d6E2n9/PykPCFAGhkKDw+nW7duxMbGsnTpUoqLi+nUqZM0ypGSkoK9vT2PPfaYNOWsVCp56qmnAE2tE21PNS8vL7p164alpaVO01g9PT2io6MZO3ZsrcKPRUVFnD9/HgsLC/bt20dISAjFxcVStWxtuw8tIyMjvLy8SEpKavKHHkGTuH769Gl8fX2ln2FBuJfc08FQcyQkJDB8+PAmHWNoaEhERASzZ8+WhrzvJH19fWkqpClGjRpFSkpKk19/c/j6+tbKDVIoFFy5cqVWLtH1tLlCSUlJOkFTYmIiMpmswRVCwu1x5swZ0tLSsLe31wkCtflDMplMyh/KycmRyvhri31qC5nW1NRgaGiIi4sLmZmZ2NnZcfjwYQIDA9m1axe5ubn07duXgwcPkpycTGBgoDQt3qtXL2xtbenfv3+tRRigSQzXVq9++OGHMTY2xtfXl0cffRSFQlGrfIChoSGPP/44RUVFdZ5PaFjHjh3x8vLCxMTknqs8LAjwAAZDly9fbvIvVG2xyXvdxo0bb9u1+vTpw6JFi6QKqaBJVFcoFA12VXZ3d8fHx4ft27czcOBAafvWrVsJCQm5K1eS3W9ycnKoqKjAwMCgziTz+Ph4Lly4gImJCba2ttJ0kzbPRa1WU1lZCWjyWzw9PSkuLsbZ2ZmMjAw6deqEnZ0dVlZW7Nmzh/bt2xMaGsrff/9NVVUVSqVSWlGanZ2NSqWiS5cuVFVV0bZtWwoKCnB1dcXY2BilUkllZWWtQp7aFZTGxsYEBQWhp6eHnp5egyN4pqamd2Tl5f1CjAgJ97IHLhi6PhFVaD1PPPEEK1as4IUXXuCFF14gLy+Pzz//nGHDhumM+Lzzzjts2rSJuLg4adtLL73Eq6++KtWM2bt3L4cPH9Yp2im0niNHjnD+/Hk6duyoU7pCS5tmeGO6YUBAgJRQ7evrS3FxMR06dKBDhw4UFRWxd+9eDh06ROfOnRkyZAiLFi2iqKiI3Nxchg4dSlVVFW5ubigUCnr16kVsbCw+Pj4EBQWxefNmqqqq8PHxYezYsVy6dAm1Wk1cXBxpaWmMHj1apxaQnZ0dfn5+2NjY1GopUlBQgImJSaMqoQsaolr1rasrhxQ0RUx37tzJxIkTOX78OKCpyWZhYYG3tze9e/fmySefrNWK6fqcN+0Hl759+zJ79uybrqRsLZGRkcybN4/ExEScnZ2ZPHmyNPXdkOrqar777js2btxISUkJISEh/Pvf/9ZZ0BQVFcUzzzxT69ihQ4cyb968W773By4YEm4PS0tLli5dyieffMKLL76IsbExERERUr86LZVKVavK95AhQ6isrOTHH39k8eLFeHp6Mm/ePFFw8TbIysoiPj6e6upqLl++XOeoi5+fHyYmJtjb2+u8Ifv6+kqB7oEDB9i+fTsuLi507twZc3NzqbJxUlISQ4YMwcPDg9jYWDw9PcnMzOTRRx8lKyuLw4cPY25uzoQJE3B1daW0tBQzMzOqqqowMTGR+iZ5eXmRnp6Ot7c3MTEx2NjYSHlmiYmJUlHFjh07Su06YmNj2bhxI25ubowfP77F+o3l5+cTGxuLg4OD1CPtfnH+/Hn27t1Lx44d6d27t6g/dAuMjY1rlWW5/ucrNDSUt956C5VKRVFREadPn2bZsmWsWrWKX3/9tdZq54kTJxIREYFCoeD48eP8+OOPpKSk3JEPjqdPn+aFF15gxIgRzJkzh+joaD755BMMDQ1vuiBh7ty5bNq0iTlz5uDm5savv/7K5MmT2bJlS622QHPnztWZ3blZv87GEsGQ0Gq8vb1ZvHhxg/t8/vnnOuUBtEaNGnVPNvu7G6WnpxMXF4e+vj6BgYENrvRxdnYmJCSEpKQk2rZtW+foSZcuXaSVZ4mJiVJOkJeXlxQMpaenU1hYSGFhIX5+frRt25bOnTuTnJxMcHCwlNQcFBTEvn37OH/+PO3bt5dGHyoqKqRRJnNzc0aOHEl6ejoBAQHSMu/8/Hy6d+/O4cOHAU0u3aBBgzA2NiYwMFBauXb9m2l6ejpqtZqrV69SVFTUYsHQiRMnOHbsGDKZjJkzZzbYHPZeExMTQ0FBAQcOHKBz585YWlqiUqmkcgZt27YVAVIj6enpNVjV29LSUuf5hx9+mCeeeIJx48bxyiuvsH37dp3vtYuLi7R/9+7dyc7OZs2aNWRnZ0u5b9pyJK09jfnDDz8QGBgoFTQOCwsjMzOTb7/9lscff7ze/yPXrl1j9erV/Pvf/5ZWR3fs2JEBAwawdOnSWh+g27ZtK626bkkiGBKE+9y5c+c4duwYoCnsebNlz42pwK6VnJwsBSNqtVoKhtzc3Lh27Rqurq5YWlpy9epVBg8eDGjq7aSmpmJvb8/YsWMpKyvDxMQEBwcHZDIZ3bt3x8HBQafyc2VlJeXl5VRUVODr68vEiRNRq9Xk5ORgbW1NYWEh5eXl/PPPPwwYMABPT0+mTJlS6347duxIVVUV9vb2LbpqzMLCAtD8wrmxivW9LigoiPT0dDp16iQFj/Hx8VLbjps1xBVujaurKzNnzuSjjz6SWtLUR/vvkJmZKQVDFy9eZPr06QwYMIDHH3+chx56qMWDV4VCwbFjx2oFLsOGDePPP/8kLi5Op8H79f755x+USqXOlLy5uTn9+/cnMjKy1jlbiwiGBOE+d31hxOu/boq4uDjkcnmt9g3Xn+/6HKJ+/foREhJCXl4e+/fvp6ioiO7du9OnTx9pP5VKRUlJCREREWRlZUmVrMPCwnT6EJaVlbF27Vqqq6vJzc1l3Lhx+Pj4kJaWxq5du+jQoQO2trakpKSgVCo5c+aMVHH+Ri4uLowYMQK1Ws2xY8e4fPkyPXv21CkP0Bzdu3fHxcUFKysrqfxDfn4+UVFRmJmZERYWds+usgoJCaF9+/ZSvSfQ/Xdv7WbW9xvtakotuVx+03wsbQB05syZBoOhzMxM9PT0pGlh0HwA+PDDD9m4cSPPPvssTk5OjBw5ktGjR+Pp6VnneVQqVaPeK7QVzK9cuUJ1dXWtxUnan6vExMR6g6HExETs7e1r5Tn5+vqyZcsWVCqVTvD23HPPUVhYiIODA4899hgvv/xyi+T/iWBIEO5z2uknuVyOt7d3k4+PjIzk0KFDmJubU1paqlOcsUOHDlJwExgYSEpKCjKZDE9PT2xtbTlz5gwZGRmAZjgcNEP/8fHxqNVqVqxYQWBgoM4ozY2/XA0MDHBycuLq1as6+QFWVlY4OTlx7tw5evbsiVqtpqCggLKysjpznbRUKhXZ2dlSBW9TU9NbDob09fVrfW/PnTsnJcS6urre8jXupOsDIdAk744ZMwZAjAo1QXl5ea2yDl988cVNWyZpV3Vqq6JrabsbKBQKTpw4werVq3nqqad0arQZGxszevRoRo8eTVpaGn/99RebNm3ixx9/pFu3bowePZrBgwfrrKT84Ycf6kz2vtHevXtp06ZNvZ0DtI8b6hxQXFwsjaxez8rKiurqaqkBuYWFBdOnT6dbt24YGRlx7NgxfvvtN5KSkvjpp59ueq83I4IhQbjPeXl5SV3kmyMnJwelUklRUREFBQU6z7m4uEhv1EeOHJHyZsLCwujZsydubm74+/tTUlKCm5sbW7duxd3dnX79+kmtMbKzs3nooYdQKBQoFArCwsJ0rqFNwMzLy8PCwoK///4bMzMzunXrxsiRI/n777+Jjo4mNDQUT09Pzp49y8mTJxk3blyt1g9qtZq9e/cSGxtLQEAACQkJrVa7ytnZGT09PSwtLe+7khByubzWL3Xh5oyNjVmxYoXOtsb0MdR+4LhxBOmrr77iq6++kh536dJFatVUF3d3d2bPns2sWbM4ceIEGzdu5OOPP+bjjz/m119/lT7ojBs3rlEFWW+syVXfCNfNRr7qev7G1aqBgYE6ixN69uyJo6MjH330ETExMTqNz5tDBEOCIDTI3d1d6iBf37A6QG5uLiUlJdLXoBlBCAgIoLCwkBUrVpCXl0deXh4dO3YkNDSUa9euoVQq+f333wkLC2PIkCGoVCqioqLIy8uja9euODo6YmlpiaWlJf/884+Uo+To6Iivry/9+/enoKAAPz8/Ll26hKmpKVeuXCE9Pb1WMFRZWcmJEyeorq6mpqaG1157DTMzs0Z9HyoqKpDL5Y2e7vL39+eFF17A0NCwzk++9wOVSkVSUhLGxsY6OV5C3fT09JqV/KstWHr9iA/AM888w/Dhw6moqGDz5s2sXbuWb7/9ln/9618Nnq+mpobi4mJKSkqorq7G2tpaZ/TPwcFBp+1OfbTTZPX1jmxM54D6uhUUFxdjYGDQYO2vIUOG8NFHH3Hu3DkRDAnC/SghIYHq6upWX6adnJxMZWVlrXYW1+vRo4dOp/pr166Rl5eHkZGRTs0oNzc36U3N1dVVKszo5eWFQqGQpr9UKhWXLl0iMDCQNm3asHz5cgBKS0tJTEzE2NiYnTt3Apo320cffRTQfFK0tbWV+pFp32BdXV1xdXUlPz+fyMhIKT+prhEfExMTHn30Uc6dO0doaGijA6GUlBT+/PNPbG1tGTNmTKPruNT3CyUjI4Py8nK8vb2Ry+WNOtfdRKFQEBMTQ0lJCQcPHkRPT4+pU6fq5KoILUfb5ubGtjvOzs5ScNW9e3fy8/NZsmQJTz75ZJ0FU+Pi4ti4cSNbt26lpKSEPn368O2339K3b18psIGmT5N5eHhgYGBAUlISffr0kZ7XlrdoqAWTr68veXl5FBYW6vxcJSYm4u3tfdtWKopgSBDuMrGxsRw+fJjs7Gx69erFI4880irXiYuL459//iEzM5NevXrpVPxuyOnTp4mKipKG97VvdNcvud+9ezdbt27F1dWVvn374u/vLy39NTY2ZvXq1QQEBBAREUFoaChVVVVcvnyZ8+fP06dPHxwdHcnOztZZ+Xbq1Cm2bdtG27ZtefTRR2t9Ss7Pzyc/Px8AMzOzegORrl276iRoN8aVK1eoqKggPT1dWsHWXFlZWSxZsoSamhqGDRvW7L5yd9KlS5fYtm2bFHCqVCqqqqru8F3dnzIyMli4cCG+vr61ppBv9Prrr7N//34WL17Mu+++C2g+ZPz5559s3LiR+Ph4/Pz8mD59OiNHjqz3Z6Sp02SGhoaEhYWxY8cOnZZVW7duvWntrfDwcPT09NixYwcTJkwANIsm9u3bd9P6RNu2bQNokaX2IhgShLtMWVmZlGx8Y8JkS6qsrCQzM7PJ19Hum5aWVu8vQO0+GRkZlJaWAv/fzPaHH34ANKMtRUVFREREsGfPHmmKLTs7m4kTJ1JRUYGFhQV79+5FoVBQVlYGaEbNhgwZUuua7u7u9O3bl9LS0hYfUfP39yc9PR0rK6tbHv1QKBTSiiJt25J7jYmJCTKZjPz8fPr06YO9vX2zkvMFXcXFxZw5cwa1Wi0VXVy9ejUGBgbMnz//pqMkPj4+DB06lHXr1jFr1ixsbGw4f/48CxcuZOjQoXzyySd07Njxpvfh5OR00xIcN5o1axZPP/007777LsOGDSM6Opq1a9fy0Ucf6dz3wIEDcXV1lYpPOjk58cQTT/DVV1+hr6+Pq6srv/32GwCTJk2Sjnv99dfx9PQkMDBQSqD+/fffGTBggAiGBOF+5OnpSZcuXSgqKsLDw6PVrmNvb0/Xrl0pLCxs0nW0eUMN5RV4enqiUqlwcnKiqKiIzZs3S/lDwcHBXLlyBRcXF/744w/CwsLw8/OjqKgIpVKJr68v5ubmmJubExUVJU0R9O3bl+DgYDw8PKSRGaVSSVRUFDk5OXTr1q3BT7NVVVUcP34chUJB9+7dG8zjycrKQi6XS8UTnZ2dpU+tt8rd3Z3Ro0dTVlbWKsXjbgc/Pz9pBKA1/4+2hqqqKmm14d1WEyo6Oprx48frtOOYNGkSEyZMaHSl5VmzZrFjxw5WrFjBiy++SFBQEP/880+rt5/p3LkzCxcu5JtvvmHTpk04Ozvz7rvv1hrdUSqVtZbtz5kzB1NTU+bPn09JSQkdO3Zk6dKlOsVL27Zty5YtW/jtt9+orq7Gzc2N559/nueee65F7l+mvjFlWxAeAAMGDAA0c95C88XExOhUIr4xifHIkSPs2bMH0NQ7GTlyJKCZVvn2228pLi7Gx8eH8PBwPDw8kMvlqFQqTp48SX5+Pk5OTmzduhWVSsXAgQPp1auXzvnT09Ol1gM9evSQCjvW5cKFC/z555+AprBkfVMO8fHxrF69GrlczuTJk0UezB3S0j+jxcXFnD17llOnTlFUVISVlRVdunShY8eODSb4Cg8GUUNdEAQdcXFxHD16VOoc35ArV65w7tw5zp07x5UrV2o9b2BgICUIGxgYcPToUdLT09HT0+Phhx8mKCiImpoali1bJv3Sy8zMZMeOHURFRZGRkcHo0aMZNWoUTk5OrFq1iqioKGnZrbW1Ne7u7shkspsGLdbW1hgbG6Onp9fgSpnCwkLUarW04ka49xUXF7Nu3Tr27dsnrXgqKipi3759rFu3Tvw7C2KaTBCE/1dUVMSpU6dISkqSprUaYm1tjb6+PjKZrM6k4m7dulFdXU1FRQW5ubmcPHmSwMBAxo4dS6dOnbCysmLZsmWAZjl+SkqK1HA1NzeX4uJijh49ylNPPcX27duJj48nPj4ef39/bGxsMDMz4/HHH6ekpOSmS7tdXFx47rnnqKmpabB3WFBQEJWVlRgYGDS4Cka4d5w9e5a0tLQ6n0tLS+Ps2bP07t37Nt+VcDcRwZAgCBKFQiElP+fm5jZYyRk0K0G0/apUKpU0DdWuXTtpyqxXr16kp6ezcuVKQLPqKyUlBVtbWzw8PAgLCyMnJweVSsXSpUsZM2YMzzzzDCdOnODo0aPU1NRQUVGBt7c358+fp0OHDuTm5pKbm4uLiwvr1q0jPT2dUaNG4ePjw5EjR6ipqeGhhx6qNf3RmLwLMzMzneXBraWwsJDKysoW7ZEm1FZVVcWpU6ca3OfUqVP06NHjnm2ZItw6EQwJgiBxcHAgNDSUrKwsXFxcGpV0qe2avXnzZi5cuABoWlxcnz/k5uZGt27duHbtGk5OTixdulRq6TBo0CDi4+NZtWoVHh4enDt3jszMTIKCglAoFLi4uKBQKJDJZMyYMYOioiL++OMPACIiIrh69Srw/x3pjxw5AmjqDwUHB7d6HZ+MjAzS0tLw9vauVZG3Pvn5+SxdupTi4mJGjx7d6onUCoWCpKQkbGxsmrxK6F5XWVnZYDsI0IyIVlZWimDoASaCIUG4x2VmZpKeno6RkVGL/FKta0XWqVOn0NfXb3BZrr29PUZGRshkMhwdHTl27JhOUPTwww8D/7+0PjU1laSkJFxcXPD19WX48OFcunSJixcvAppVSoMHD6aiooKff/6ZqqoqQkNDdapKa4syZmdnS/dmZmaGh4cHO3bs4MKFC4wYMQITE5Nb/r7Upbq6mo0bN5Kbm4uvry9PP/10o44rKSmR8lS01bpb0/Hjx9m7dy+mpqY8++yzt1Qn6V5jbGyMlZVVgwGRlZVVq6+2Eu5uIhgShHtcbGwsR48exdLSEpVK1ag6Ik2xd+9eDh8+jImJCQqFgm7dutW5X69evaRpqOTkZE6cOIG9vT36+vo6dX+Cg4NJS0vD1taW1atX4+fnx5NPPknnzp2lukf29vZSiX/QTMF5eHhw+PBhPD09GT16NCqVisDAwFpNRJ9//nkiIyOpqqri0qVL5Ofnt9qKMJlMJi3PbsqoQps2bRg8eDDFxcXSyFpr0tYzqqyspLq6utWvdzcxMjKiS5cu7Nu3r959unTp0qqjQhMnTpSa9t7om2++4bHHHpMeR0ZGMm/ePBITE3F2dmby5Mk89dRTtY5bvHgxK1euJCcnB39/f958802dSvExMTGsXr2akydPcu3aNRwdHRkwYACzZ8+Wpravt3btWpYvX05ycjLm5uZ07NiRH3/8sc573rBhA2+//fZNX7d2EcbmzZtZtmwZycnJqNVqnJycCA0N5bXXXpMWM1RUVLB48WK2b99Oenq61OIlPDycV1999abXulUiGBKEe1xhYSGgWTGjLUzY0udXq9WUl5dLhRHro23rcebMGUAz6nHjL9++fftSU1PDwoULUavVyGQyDhw4QFBQEI888ght2rTB3t5ems4xMTHhiSee4ODBg4BmBdvIkSPrHd0wNzcnODiYnJwc3NzcyMnJITExkU6dOrX4Emp9fX1GjRpFRkZGk+rtyOVynV9cra1bt26YmZlhb2/fYPL4/apjx44kJCTUmUTt7u7e4h8gbvSf//xHKj6qtXTpUnbv3i0VIwVNdfcXXniBESNGMGfOHKKjo/nkk0+kZsVaixcvZt68ebz66qsEBgaydu1ann32WdauXSstetixYwfJyclMnToVb29vUlJS+Pbbb4mOjmb16tU6hRAXLFjA77//zvPPP0/Hjh0pKiri0KFD9b6efv36sWbNGunxgQMHWLRoEb/++mut+l0///wz33zzDZMnT+all15CrVaTkJDAli1byM7OloKh2bNnc+7cOWbMmEH79u0pLi4mNjaWv//++7YEQ6LOkPBAup/qDEVFRZGSkoKFhQUdOnRoVBfspjh16hSJiYkYGRnRsWNHvLy8bnrMkSNHSE1Nxc7OjsrKSnJycmjfvr1OnaCTJ0+Sm5tLTEwMFRUVBAUFMWbMmHrPmZ6eztmzZ2nTpk2jmzKmpqby+++/A9C/f3+xYugecr/XGRowYAC+vr78/PPP0rbp06dTVFTE2rVrpW3vvfce+/fvl3rAKRQKevXqxbhx43jzzTcBTSHDYcOGERAQwLx58wBNXpqtra3ONffu3csLL7zA8uXL6d69O6DpATZs2DB+/vlnwsPDm/VatCNFR48erXXN3r17Ex4ezty5c2sdp1Kp0NPTIyUlhUGDBvHf//5XqkV24z6tTYwMCcI97sZGqi3t+p5jAAcPHiQ1NRUHBwc6d+5cZ0Jur1696NWrF/v27eP06dNA7c7VXbt2JScnh7NnzwJws89lbm5uN53uunr1KhUVFfj4+CCXyzE1NcXY2JjKyso6pwaaKjExEYVCgb+//z3ZYPVBZmlpSe/evenevTtVVVUYGxvfsYTp6Ohorl69yiuvvCJtUygUHDt2jNdff11n32HDhvHnn38SFxdHcHAw0dHRlJSUEBERIe0jl8sZOnQov/32mzTaemNQAkjT1dnZ2dK2DRs24O7u3uxA6GZKSkrqXVigDXK0+XN1jVrerkatouiiIAhNok18joqKIi8vr8F9XVxccHZ2xtjYGEdHR1asWEFkZKT0vIODAxEREfTq1Yvw8HBKSko4evSo1O36RlVVVfUGTRkZGfz+++/88ccfUoDl4ODAtGnTmDx58i3n5qSkpLBixQr+/PNPzp07d0vnEu4cIyMjLC0t7+jKsa1bt2JiYiKNfoFm+re6ulpqfqvl5+cHaALx6/++cT9fX1+dvoZ1OXnypLSv1tmzZ/H39+eHH36gZ8+eBAcH8/TTT0srQ29VUFAQq1evZu3atfX2QPTx8cHU1JTPP/+c/fv3t8p0/82IYEgQhCbRfnpzd3e/aW+n9u3bM3bsWMaPH8/Ro0dJTEzk/PnzOvsEBQUxcOBAXFxc2LdvH7t372bLli1kZGTo7BcbG8v8+fPZsWOH1Oj0egqFAqVSCWgCo6NHj1JdXY29vT2enp7IZLJbednSuW/8WhCaoqamhp07dzJgwABMTU2l7drVbjeOoGofa58vLi7G0NCw1uo37YIDbQ7hjYqLi5k3bx49e/aUcvtA01T5n3/+YcuWLXz44YcsWLCAiooKpkyZ0iKVuf/zn/9gZWXFu+++S3h4OAMGDOCTTz6RSmKAJs/v008/JT09neeff55u3boxevRoFi1aRHl5+S3fQ2OIaTJBuM8dP36cCxcuIJfLCQwMJDQ09JbO17lzZzw8PDAyMqKwsJDly5cDmiH466fTtGxtbTE2NsbDw4OEhAT8/Pz45Zdf8PPzk5bba1VUVABQWlpKfHw8NTU1UmJyfHw8lZWVnDhxgp49e0or16qrqzl48CAFBQUMGTKEgoICLl68yKlTp7C1tb1pFe3G8vHxYdy4cSgUCp1fJoLQFIcPHyYvL09nmut69QXt12+vax/tiGldzymVSl5//XUqKir49NNPax1XXl7OggULaNu2LaD5gDJgwADWrFnDs88+27gXVg9/f3+2bt3K0aNH+eeffzhx4gTLly9nw4YNrFy5UvpZGjp0KA899BD79+8nKiqKY8eOMX/+fDZv3sz69et1AsfWIIIhQbjPZWRkkJKSAlBnHkFTOTk5SXlCmzdvJikpCUBKSK2LqakpgwYNokuXLuzdu5ecnBzy8vLw9fXF0dFR+pTbsWNH9PX1MTY25tChQ1RWVkrBUHBwMNnZ2QQGBuosu8/OziYuLg4zMzMOHz5Mnz59KCoqkqZDWopMJhNBkHDLtm7dirW1da0cHe3/6RvrIWlHZ7T/ly0tLamqqqKqqkpnZFa73/U/G1rvvfceJ06cYOnSpbXy7qysrLC3t5cCIQBHR0d8fHzqna5uKkNDQ/r27Uvfvn0BOHToEDNmzOCHH37g+++/17mXkSNHMnLkSNRqNd999x0LFy5k3bp1PPPMMy1yL/UR02SCcJ9zdHTE3Nwca2tr7O3tW/zclpaWWFpaSoUW66unYmdnR0BAAH5+fsjlctq2bcvKlSvZtm2btE/79u0ZOnQoRUVFyOVyvL29pecCAgKYOXMmffv21UmqtLW1xdvbm7S0NIqLi8nPz+e5555j+vTpuLi46NxDSkoKv/76Kzt37kShULTo90IQbqayspK9e/cyePDgWvWxPDw8MDAwkD5caGkDEm2ej/Zvbe6QVmJiImZmZrUWNHzxxRf89ddfzJ8/v85VmPX131Or1a2WvNy7d2/atWtX6zVcTyaTMW3aNKD2a20NYmRIEO5zvXr1wtXVFblc3uLL7sPCwqSAIyUlhcjISGQyGZWVlfX293rkkUcIDQ1lzZo1KBQKrK2t+euvv/D396d9+/aYmpoyfvx4qqurpcrRZWVl5Obm0qZNm1qruExMTOjXrx81NTVkZmbStm3bevt9Xbx4kfT0dNLT0+nQoUOrFWMUhLrs27ePsrIyhg0bVus5Q0NDwsLC2LFjB5MnT5a2b926FQcHB2klWGhoKBYWFmzfvl3aplQq2bFjB3379tWZJvvll1/47bffmDt3rjQqc6N+/fqxceNGqQEywLVr10hKSmL06NG3/Jpzc3NrfQirrKwkMzNTSg4vLS2VRoSvpx3Rvh21sUQwJLQ4pVLJb7/9RmRkJJcvX0apVOLv78/s2bN1CozVp64cD3t7ew4fPtwat/tAaKg2UF31SJrC09MTgHPnzqFWq1Gr1ZSVldV7Xj09Pezt7enSpQtqtVqqFl1ZWSlNQ+nr66Ovr3l7KisrY8OGDSQlJdGjRw8GDx5c65zm5ubS0HpDidI+Pj7ExMTg5eXVIlOGgtAUW7ZswdXVtd7p5FmzZvH000/z7rvvMmzYMKKjo1m7di0fffSRNEpjaGjIzJkzmTdvHra2tlLRxbS0NL755huda3311Vc89thjeHt7S4VQAZydnaUPDAMHDiQoKIgXX3yRl19+GUNDQ3744QdsbW0ZN27cLb/mYcOG8fDDDxMeHo6joyPZ2dksX76cgoICJk2aBGgq1s+cOZNRo0bRpUsXTE1NSUxM5Oeff8bCwoJRo0bd8n3cjAiGhBZXWVnJTz/9xMiRI5k2bRr6+vps3LiRKVOmsGjRolpJs3WZOHGiToLhjUPKwq1LSkri+PHjZGRkEBoaWmdPsqbw9vampqYGmUyGiYkJv//+O66urjz00EN1jkiFhYWRlJQkjfTUF8QUFRWRnJwMUGuF2Y1utmLM39+fl19+GQMDg9tWv0QQAKmq86RJk+r9f9q5c2cWLlzIN998w6ZNm3B2dubdd9/VqT4NMHXqVNRqNcuXLyc3Nxd/f39+/vlnnQ+S2g+P27Zt05mKBk215xdffBHQ1Cj65Zdf+Oyzz3j//fepqamhW7dufP311y2StDx79mz279/P559/Tn5+PjY2NgQEBPD7778TFhYGaD5QjR8/nsOHD7N27VrKyspwcnIiLCyM559//raM4IoK1EKLUyqVlJaW6iTyqdVqHn/8cczMzKTVR/UJCAjgzTfflOaLW8P9VIG6uU6dOsXWrVsBTS2TuvofNdfKlSulXIdhw4Y1uILtxIkTZGdnS/lEddmzZ480rH59FWvh/iV+RoXbSYwMCS1OLpfXWtEgk8lo164dp06dukN3JdzI0tKS9u3bk5mZSZs2bVr03G5ubuTm5uLi4kJWVha//fYb7dq1qzOQqavxq7bPmrOzMzKZjIEDBzbquiqViosXL6JUKmnfvr001SYIgtAQ8U4h3BYqlYrTp0/Xu3LhRtrmfiYmJoSHh/Pmm2/i6urapGteX931RpmZmbVWGj1o2rZtS9u2bSkuLq61BL2goECq49Mc/fr1o0uXLpw9e1b6ZG9hYUFJSUmtRo43KioqYtmyZeTn5/P4448THBzc4P5KpVKaart8+bLU12n06NF06NCh2a9BEIQHh5g0F26L5cuXk5yczJQpU26678iRI/nggw/4/fffefXVVzl58iRPPvlkrfobQsu4MRDatm0bv/32G7t27bql81pYWGBubo6zszNGRkbY2Njw888/s3v37gaP0yZfBwQEsGfPnnorTldWVrJhwwYWLlwoLUe+WWE6QRCEuoiRIaFRSkpKdJr71cfd3b1Wz5/jx4/z5ZdfMnXq1DqnRG703//+V/q6W7dudOnShdGjR/Pnn382qRpqQ7kGDY0aPciysrKIi4ujvLycixcv0rdv31rLXZuiU6dOODo6olAoWLVqFQqFgvT0dBISEnBycqqzKKKLiwsREREkJCRQXFzM8ePH6datW63ludnZ2cTGxgJw6dIlTE1N8fX15cknn0SpVOoUkbveuXPnuHz5MsHBwfXmKAmC8GARwZDQKHv27OHtt9++6X6bNm3SqdJ78eJFXnjhBR555BHeeOONZl27Xbt2eHt71+ppJbQ8Z2dnAgMDiY+Pp127drcUCGm5urqiUCgIDg4mOTkZKysr/vjjD7y9vXnyySdr5fXIZDK6dOmCubk5165do127dlhbW9c6r6OjIx07duTq1auUl5eza9cufHx8CAsLk1YfVlZWcuDAAQoKCujXrx82NjZs2bIFhUJBXl6eCIYEQQBEMCQ00ujRo5tcgOvKlStMnz6dwMBAvvjii1uathCLHm+fxx57jD59+ki5PWfOnCE1NRUTExO6dOmCnZ1dk89paGjIsGHDqKioYOnSpYBmFGrfvn2YmZnx0EMP1TomICCAtm3bSkvgc3NzuXjxIi4uLvj6+mJsbMzIkSPJzMxk586dZGZmkpKSgr6+vlTPKj09naioKEATlGmbVJ49e/aeDoQqKiq4du0ajo6Ord6zSRAeBCIYElpFTk4OU6dOxd7enoULF9aaOmuKCxcukJKSwuOPP96Cdyg05Pok5+TkZGJiYgBNtefevXs3+7wmJib06NGDpKQk9PT0OHr0KK6urnh6eta5ou36WkBHjhzh9OnT6Ovr8+KLL0pTbM7OzgQFBZGWlgZoGrdqOTg44OHhQWFhIUVFRfzwww/07NmT8PDwW0oQv9N2797NmTNnaN++PWPHjhX5UYJwi0QwJLS4yspKpk+fTl5eHnPmzKnV7K9Tp07S1wMHDsTV1VUaLVi8eDFpaWl0794dW1tbEhIS+PHHH3F2dq5VeEy4PbRTZfr6+rcU1Gp17tyZzp07s2TJEiwsLDA0NGTJkiWEhYU1uITezMwM0DSKvXDhAnK5nJCQEAwNDenevTuWlpYUFRURFBREdXU1KSkpWFlZ8dRTT5GTk8Ovv/4KaKZutcXetOLj48nOziYoKOiuD5LUajVZWVmAZlVkTU2NKEoqCLdIBENCi9NOZ4CmvPyNLl26JH2tVCpRqVTSY29vb3bv3s327dspKyvDxsaGvn378sorr7RoB3Kh8UJCQjA2NsbU1JQePXpw9OhR0tLScHBwaFQ18fp069aNwsJCKdH92rVrbNq0iR49etRZ9iA8PJw2bdpQVlbGli1bAE1l8o4dOwKa3DKto0ePsnv3bkxNTZk6dSpOTk506tSJxMTEWonVeXl5rFmzBpVKRVlZGYMGDWr2a7odZDIZgwcPJiEhAR8fHxEICUILEMGQ0OLatGmjE/A0ZN++fTqP+/fvT//+/VvjtoRmcnNz0ymHn5SUxOXLl4mPj8fZ2VknYb4pgoODqampoaioiGvXrqGnp0dxcTHnz5+npKREahqpZWRkREBAAElJSchkMtRqdb0J3uXl5YAmt2bPnj0EBQUxYsQIFApFrdEtAwMDzMzMKCkpuWfybzw9PaWecIIg3DoRDAmC0CTagMHKygp9fX2ps3RDzWDro6+vz2OPPUZMTAxbtmwhKCiIw4cPExMTw8iRI/Hx8al1jI+PD5MnT0atVtcbEHTt2hUDAwOuXr1KQkKCdFxdwZOlpSUTJ06koKAALy8vTp48SUxMDD169CAoKKjJr0kQhHuPCIYEQWiSkJAQbGxssLKyIicnh2PHjgHQq1evWrk4TTmnnp6eVD6hrKyM1NRUcnJy6NGjR639PTw8GjyflZUV4eHhHDx4kGvXruHq6so333xD27ZtefTRR2t1rHdwcMDBwYHKykr27NmDQqGgurpaBEOC8IAQwZAgCE3i6+srtVXZvHkzJSUlAI0qytmQ4OBg5HI5crkcS0tLDh8+jI+PD9XV1fTq1avJXeb19PTo168fffr0YcOGDahUKi5duoSTk1O9uU5GRkZ069aNY8eO6ST6C4JwfxPBkCAIzebm5kZxcTGgyRVbt24dAP7+/oSEhDT5fO3bt8fLy4tdu3bh5uZGTU0Ne/fupV27drUqUDdEoVCgp6eHvr4+enp6BAcHU1hYiIWFhZRPVBeZTMaAAQPo1avXPZM/JAjCrRPBkCAIzdalSxe6dOkCwJYtW6RpLhMTk2YFQ9pjR44cSWxsLH/99RdBQUFcuHCBzMxM/Pz8CA0NbfD4q1evsn79eszNzRk9ejQ2NjZSFev09PSbFluUyWQiEBKEB4wIhgRBaBE2NjYYGBggk8mwsrLizz//xM7Ortl94Dp06ICPjw9FRUUsWbKEmpoaKioqUCqVDfa4S01NpbCwkMLCQrKysqS6Qc7Ozjg7OzfrXgRBuL+JYEgQhBYRHh6OpaUlarWaCxcucOnSJWQyGfb29lItoKYyMzOjpqYGOzs7rl27hpmZGbt27aJNmzZ11iIC8PPzIzk5GVNT0zqrWguCINxIBEOCILQY7dRYamoqoFnVlZ+fz5o1a/D29qZ79+5NPqeVlZXUxT4+Ph5ra2suX75MXFwcYWFhUmVqLScnJ55++ulbfzGCIDwwRDAkCEKLCwkJwdLSEiMjI3bv3g2AXC7Hz8+v1rL2xmjTpg12dnZYW1ujUqnYunUrANbW1lLOkiAIQnM1ba2qIAhCI3h5edGvXz+MjIwwNzdHJpNhYWHBkiVL2LVrV7POaWJiQufOnXFycsLIyAh9fX3s7OzIzs6u1f9OEAShKcTIkCAIrSY0NBR9fX1kMhnbt2+nsrKS7OxsDh06hLm5OZ07d27yOdu0acOMGTNQq9VUVlaydu1a8vLyCA8PF61cBEFoFhEMCYLQqkJCQigsLCQoKIiUlBT09fXZt28fzs7OuLq64uTk1ORzaleInTlzhtzcXABycnIafXxaWhpRUVG4uLgQFhaGXC5v8j0IgnD/ENNkgiC0OmtrayIiInjmmWcoLS0FNM1Ujx49WqtZb1MEBATQrVs32rZtK3Wtz8vLkwKk+pw9e5bz58/z999/33RfQRDuf2JkSBCE28bS0pKgoCDs7e1RKBScPXuW0NBQdu7cibu7e5N7gZmYmDB06FDpcUJCAn/99RdKpZLHHnuM4ODgOo/z8PAgOjoab29vjIyMOHfuHHZ2dvUu1xcE4f4mgiFBEG6rXr16AbBhwwbat2/PpUuXKCsro6SkBFNTU7y9vZt97vT0dMrKyqSv6wuGQkJC8PLywtjYmCNHjhAZGYmxsTGTJk0ShRkF4QEkpskEQbgjHn30UYKDg6murgZAqVTy559/8s8//zT7nEFBQQQFBdGuXTuCg4O5du0aZ86ckfqnXc/S0hJDQ0Pp+jU1NezYsYOTJ082+/qCINybxMiQIAh3hLm5OYGBgeTl5ZGXl4dcLicwMJDk5GSKi4ulitZN4eDgwJgxYwCoqKjg559/prCwkJCQELp27Yq7u3utY7SFG5OSkkhMTMTExISuXbu2yGsUBOHeIEaGBEG4o3r37o2/vz/l5eWUlJSQlJTEiRMniImJ4cKFC7d0bqVSCUBxcTGrVq0iLi6u1j4WFhb07NkTf39//P39RRFHQXgAiZEhQRDuuMDAQAIDA9m9ezcJCQm4ubkRHx+PpaUlZmZmeHh4NPmcJiYmPPHEE5w6dYqMjAwqKiqIj4+noqKiVsAjk8no3r17s9qFCIJw7xMjQ4Ig3DUeffRRxowZg6GhIWlpaSgUClasWMHx48dRKBRNPp+rqyvdu3fH0dGR4OBgsrOziY+Pb4U7FwThXiZGhgRBuKsEBQWhVqtxcnLi7Nmz6Ovrc/bsWSoqKujbt2+Tz+fk5MTIkSM5fvw45eXlhISEsH79esrKyhg0aFCzij4KgnB/EcGQIAh3neDgYHx8fDA0NCQ1NZXU1FSCgoLYv38/rq6uBAQENOl8MpmMHj160KNHDy5cuMC5c+cAuHz5sgiGBEEQwZAgCHcnU1NT+vbtS1RUFN7e3mRkZHD+/HlMTU2ZPHkyDg4OzTqvs7Mz7u7ulJWV4eXl1bI3LQjCPUkEQ4Ig3LX09PTo2bMnAGvXrgU0K8QuX75MVFQUvXr1wtbWtknntLGx4ZlnnkGlUmH4f+3df1AU5/0H8PcBB4j8OBAwAQUUPAaEHGBErYAMBIIBgtVoiZGaanQsRpI0thK1tnGs2NGkqClqhWSIGjONIg0qhgiKNcbEFkwTqFbPGJEB+SUeauC4Y79/+OWay8Gh9OBO9/2aYfSe/Tx7n93Hk8/tPrtra2vynIno4cNiiIgeCtOnT4dMJoOdnR0uXrwImUyGEydOQKFQICAg4IHWZWPD//qI6L94NRkNiezsbAQGBhr8nDp1asC+3d3deOuttxAVFQWFQoGMjAxcuHBhGLImS+bl5YWEhATY2tpi9OjRaGlpQXd3N8rLy3HmzBlzp0dEDzF+PaIhM3bsWGzZskWvzd/ff8B+OTk5KC4uRnZ2Nry9vZGfn48XX3wRJSUlg54nQo+OqVOn4ty5c9BoNKiqqgIAuLi4QCKR4Mknn4RUKjVzhkT0sGExREPG3t4eYWFhD9Tnxo0b+PDDD7FmzRrMmzcPAKBQKBAfH4/CwkKsXLlyCDKlh83kyZNRU1ODlpYWtLS0wMXFBWVlZWhvb8f06dMf+DEeRCRuPE1GFuX06dPQarVITk7WtTk6OiIuLg6VlZVmzIwszcSJE/HTn/4UiYmJOHfuHACgo6MDX331Fb7++mszZ0dEDxMeGaIhc+3aNTz55JPo7OyEXC5HZmYmnnrqKaN9lEol3N3dIZPJ9Nr9/f1RUlKCnp4eWFndXw0fHx/f77KGhgY8/vjj97UeslwymQwymQyCIODKlStwc3PD+fPn4erqira2NsTExEAikZg7TSKycCyGaEgEBQUhNDQUAQEB6OjowP79+7F8+XJs3boVSUlJ/fZTqVRwcnIyaHdxcUF3dzfu3r0LR0fHoUydHkJhYWEYOXKk7iozpVIJpVIJV1dXTJgwASNGjDB3ikRkwVgM0X3p6OhAU1PTgHFjx46Fra0tFi5cqNceFxeH9PR0bNu2zWgxBKDPb/KCIDxYwgDKy8v7XWbsqBE9nCZMmAA7Ozt89dVXurZr167h4sWLiIqK4pFAIuoXiyG6L59++ineeOONAeOKi4sRFBRk0G5lZYXExERs3rwZnZ2dsLe377O/s7MzVCqVQbtKpYJUKoWDg8ODJ0+i4ePjA29vbwQEBKChoQFffPEF1Go1JBIJnnvuOXOnR0QWisUQ3ZfZs2dj9uzZ/9M67ufojr+/P1pbW9He3q43b0ipVGLcuHH3PV+IxMva2hpBQUEYMWIEamtr0draCjc3N3z00Ufw9fXF5MmTOY+IiPTwNwsNi56eHnzyySeYMGFCv0eFACAqKgpWVlYoLS3Vtd25cwcVFRWDemI5iZefnx9eeOEFPP/882hra0NtbS1KS0tx8+ZNk71Hc3Mzqqqq0NbWZrJ1EtHw45EhMrn6+npkZ2cjJSUFPj4+uHXrFvbv349vvvkG27dv14tNSEiAl5cXCgsLAQCjR49Geno6tmzZAhsbG3h5eeHdd98FAIN5SEQDcXV1haurKzo6OlBTU4OgoCCTTcDXaDQoKipCY2MjJkyYgPnz55tkvUQ0/FgMkcmNHDkSjo6O+POf/4y2tjZIpVKEhIRg9+7diI6O1ovVarXo6enRa8vOzoaDgwNyc3PR0dEBhUKBwsJC3n2aBm3SpEkICAiAg4MDpFIpmpqaUFtbCycnJ4SFhcHa2trcKRKRGUmEwVymQ/SQ672azNgVZ/ToOn78OP7zn/+gubkZsbGxgz4F29TUhLq6Ovj5+WHUqFEmzlLc+Bml4cQjQ0QkOq6urmhpaQEA3Z+D4enpCU9PT1OlRURmwmKIiEQnPDwcGo0Gzc3NUCgUKCsrw+XLl5GYmIiAgABzp0dEw4zFEBGJjpWVFaZMmQLg3sOBP//8cwBAVVUVWlpaMGnSJEilUnOmSETDiJfWE5GoyWQy3eM8tFotPvnkE1y5csXcaRHRMGIxRESiZmdnh2effRZpaWm4dOkS7Ozs4OzsbO60iGgY8TQZEYmeRCLBhAkTsGTJEkilUri7u5s7JSIaRiyGiIj+Hx/mSiROPE1GREREosZiiIiIiESNxRARERGJGoshIiIiEjUWQ0RERCRqLIaIiCzE7du38fnnn6OmpgZ8hjbR8GExRERkIaqrq1FWVoYDBw6gvr7e3OkQiQaLISIiC2Fvbw8AkEqlsLW1NXM2ROLBmy4SEVmIiIgIuLq6wtHREZ6enuZOh0g0WAwREVkIa2trBAQEmDsNItHhaTIiIiISNRZDREREJGoshoiIiEjUWAwRERGRqLEYIiIiIlFjMURERESixkvrSZSampqg1WoRHx9v7lSIqA8NDQ2wtrY2dxokEjwyRKJkZ2cHGxvTfhdoaGhAQ0ODSdc53LgNluFR2Abgf9sOGxsb2NnZmTgjor5JBD4NkMgkeo8ylZeXmzmTweM2WIZHYRuAR2c76NHHI0NEREQkaiyGiIiISNRYDBEREZGosRgiIiIiUWMxRERERKLGYoiIiIhEjZfWExERkajxyBARERGJGoshIiIiEjUWQ0RERCRqLIaIiIhI1FgMERERkaixGCIiIiJRYzFEREREosZiiIiIiESNxRARERGJGoshIiIiEjUWQ0QD+Pbbb7F48WKEhYVh2rRp2LBhAzo7O++r76FDh5CUlITQ0FCkpKSgtLR0iLPtW2lpKTIzMzFjxgyEhYUhNTUVH3zwAXp6eoz2y8jIQGBgoMGPUqkcpsz/q6ioqM9ctmzZMmBfSxmH/vZnYGAgjhw58sD9hmMcvvvuO6xbtw5paWkIDg5GSkpKn3GVlZWYNWsWQkNDkZCQgH379t3X+ru7u/HWW28hKioKCoUCGRkZuHDhgik3gWhANuZOgMiSqVQqLFy4EF5eXti2bRva2tqQk5OD9vb2AX8JHzt2DNnZ2Vi6dCmmT5+O48eP47XXXoOTkxOioqKGaQvuee+99+Dl5YXf/OY3GDVqFL744gv84Q9/QF1dHVatWmW0b0REhEHMmDFjhjJdo/Lz8+Hk5KR7PXr0aKPxljQOv/vd73D79m29tsLCQpSVlWHatGlG+5prHC5duoTKykooFAr09PSgr8dZVldXIzMzE2lpacjOzkZVVRU2bNgAW1tbzJ071+j6c3JyUFxcjOzsbHh7eyM/Px8vvvgiSkpK4OHhMVSbRaRPIKJ+7dq1S1AoFEJra6uu7eOPPxbkcrlw+fJlo32TkpKErKwsvbZFixYJc+fOHZJcjflh/r02btwohIaGCl1dXf32W7BggbB06dKhTO2+HTx4UJDL5X1uizGWNA59iYuLE5YsWWI0xpzjoNVqdX9ftWqVkJycbBCzePFi4bnnntNrW7t2rTB9+nS9/j/W2NgoBAUFCXv37tW1dXR0CJGRkcLmzZtNkD3R/eFpMiIjTp06hWnTpsHNzU3X9vTTT8PW1haVlZX99qurq8OVK1cMTimkpKTgX//6F9ra2oYs5778MP9eQUFB6OrqQnt7+7DmMpwsbRx+rKqqCtevX0dqaqpZ8zDGysr4rwm1Wo2zZ88iOTlZrz01NRXNzc2ora3tt+/p06eh1Wr1+jo6OiIuLs7o54vI1FgMERmhVCrh7++v12ZrawsfHx+j8zWuXLkCABg/frxeu7+/PwRB0C03p3/+85+QyWQYNWqU0bgvv/wSYWFhCA0NxYIFC3Du3LlhyrBvKSkpCAoKQnx8PHbt2gWtVttvrKWPw+HDhzFixAjEx8cPGGtp49Dr2rVr6O7uNtjHAQEBAGD0c6JUKuHu7g6ZTKbX7u/vj2+//XbAOW1EpsI5Q0RGqFQqODs7G7Q7Ozvj1q1b/fbrXfbjvi4uLnrLzeXrr79GUVERli9fDmtr637jJk+ejLS0NPj5+aGpqQkFBQX4xS9+gT179iA8PHwYMwY8PDywYsUKKBQKSCQSVFRUIDc3Fzdu3MC6dev67GPJ46DRaHDs2DHEx8fDwcHBaKwljcOP9bePe18b28cqlUpv/lcvFxcXdHd34+7du3B0dDRhtkR9YzFENAiCIEAikQwY9+MY4f8nn95P36HS3NyMrKwshIaGYsmSJUZjs7Ky9F7HxsYiJSUFeXl52L1791CmaSA6OhrR0dG611FRUbCzs0NhYSGWLVsGT0/Pfvta4jh89tlnaG1t7ffqrB+ypHHoT3/7cqB93NdyoY9J2kRDiafJiIxwdnaGSqUyaO/o6OjziFGv/o489K7LWN+h1NHRgSVLlsDe3h47duyAVCp9oP4ODg6YMWMGampqhijDBzNz5kxotVr8+9//7nO5pY4DcO8UmUwmG9QVbZY0Dv/LPu7v86VSqSCVSgc8YkZkKiyGiIzw9/c3mPOgVqtx7do1g7lEP9Q7f+LHc1KUSiUkEonB/Irh0NXVhV/+8pdoaWlBfn4+XF1dB7Weh+lbuyWOAwB0dnaivLwcSUlJD1yQ9rKUcfDx8YFUKjXYx5cvXwYAo58Tf39/tLa2GkziVyqVGDdu3ICTt4lMhf/SiIyIiYnB2bNncfPmTV3bp59+CrVajRkzZvTbb+zYsRg/fjyOHj2q13748GE88cQTfV7dNZQ0Gg1eeeUVXLhwAfn5+fD29h7Ueu7evYvKykqEhoaaOMPBOXr0KKytrREcHNzncksbh14VFRW4c+fOoK8is6RxsLW1xdSpUw1uZHn48GF4eHj0OzbAvVOdVlZWen3v3LmDiooKo58vIlPjnCEiI9LT07F3715kZmYiMzMTra2t2LRpE1JTU/W+8a5evRrFxcV6lxFnZWXhtddeg4+PD37yk5+gvLwcn332GfLz84d9O9avX48TJ07g17/+NTo7O3H+/HndsoCAADg6Ohpswz/+8Q8UFBQgISEBXl5eaGpqwnvvvYfm5mZs3bp12Ldh8eLFmDp1KuRyOQCgvLwcf/3rX/Hzn/9cd3M+Sx+HXiUlJfDy8sKkSZMMllnaOHz//fe6y9zr6+tx+/ZtHDt2DAAQGRkJNzc3LF++HAsWLMDatWuRmpqKqqoqfPTRR1i/fr3e0Z3ebSgsLARw74aZ6enp2LJlC2xsbODl5YV3330XALBw4cIh3zaiXiyGiIxwdnZGYWEhNmzYgBUrVsDe3h4pKSlYuXKlXlxPT4/BJd4zZ85EZ2cndu7ciYKCAvj6+uJPf/rTsN/1GLh3PxcA2Lx5s8Gy999/H1OmTDHYBg8PD6jVarz99ttob2/HiBEjEB4ejjfffBNPPPHEsOXea9y4cThw4AAaGxvR09MDPz8/rF69GhkZGboYSx8H4N7cmr///e9YuHBhn5OHLW0cWltb8corr+i19b7u/bcTHh6OvLw8vP322yguLsZjjz2GtWvXGtx9WqvVGlwun52dDQcHB+Tm5qKjowMKhQKFhYW8+zQNK4lgKSeeiYiIiMyAc4aIiIhI1FgMERERkaixGCIiIiJRYzFEREREosZiiIiIiESNxRARERGJGoshIiIiEjUWQ0RERCRqLIaIiIhI1FgMERERkaixGCKiR45Wq4VarTZ3GkT0kGAxREQm8d133+GNN95AYmIiFAoFoqOjsWzZMly8eFEX09bWhpCQEOTm5hr0VyqVCAwMxPvvv69ra25uxrp16xATE4OQkBDExcXhnXfegUaj0cVcv34dgYGB2L17N/Ly8hAXF4fQ0FCcPXsWXV1d2LRpE9LS0jBp0iRERkbiZz/7GY4fP27w/iqVCqtXr0ZkZCTCw8OxdOlS1NXVITAwENu3b9eLvXr1Kl5//XVMmzYNISEhmDlzJvbt22eCvUhE5sCn1hORSTQ1NUEmk+H111+Hm5sbbt26hUOHDmHevHk4dOgQxo8fDzc3N8TGxqK4uBhZWVmwsvrv97GioiJIpVKkpqYCuFcIzZ07F1ZWVli+fDl8fHxQXV2NHTt2oL6+Hjk5OXrvv2fPHvj5+WHVqlVwdHSEr68v1Go1bt26hUWLFmH06NHo7u7GmTNnsGLFCuTk5GDWrFkA7j0pftmyZfjmm2/w8ssvY+LEiaiursZLL71ksJ2XL19Geno6Hn/8caxatQoeHh44ffo0NmzYgJs3b+Lll18eup1MRENDICIaAhqNRlCr1UJiYqKwceNGXXt5ebkgl8uF06dP68VGRUUJK1as0LX99re/FcLCwoT6+nq99RYUFAhyuVy4dOmSIAiCUFdXJ8jlcuGpp54S1Gr1gDl1d3cLq1evFmbNmqVrP3nypCCXy4UPPvhAL37Xrl2CXC4Xtm3bpmtbtGiREBMTI3R0dOjFrl+/XggNDRXa29sH2jVEZGF4moyITEKj0WDnzp145plnEBISguDgYISEhODq1atQKpW6uJiYGHh4eKCoqEjXdvr0aTQ1NWHOnDm6tpMnT2LKlCnw9PSERqPR/cTExAAAvvzyS733j4uLg1QqNcirtLQU6enpCA8PR3BwMCZOnIgDBw7o5dS7rpkzZ+r1TU5O1nvd1dWFs2fPIiEhAfb29gZ5dXV14fz58w+454jI3HiajIhMYtOmTdi3bx+WLFmCyZMnw8XFBRKJBGvXrkVXV5cuzsbGBs8++yz27t0LlUoFZ2dnFBUVwcPDA1FRUbq41tZWnDhxAhMnTuzz/W7evKn32sPDwyCmrKwMr776KpKSkvDSSy/B3d0d1tbW2L9/Pw4ePKiLa29vh42NDWQymV5/d3d3vdft7e3QaDTYs2cP9uzZc195EZHlYzFERCbx8ccfY9asWfjVr36l137z5k04Ozvrtc2ZMwcFBQU4cuQInnnmGVRUVGDhwoWwtrbWxbi6uiIwMBCvvvpqn+/n6emp91oikfSZ05gxY5Cbm6u3vLCwUC9OJpNBo9Ggvb1dryBqbm7Wi3N2doa1tTXS0tIwf/78PvMaM2ZMn+1EZLlYDBGRSUgkEoPTVCdPnsSNGzfg6+ur1+7v7w+FQoGioiL09PRArVZj9uzZejGxsbGorKyEj48PXFxc/qecflgINTc3o7y8XC8uMjIS+fn5OHr0qF6Rc/ToUb24ESNGYMqUKaitrUVgYCBsbW0HlRcRWRYWQ0RkErGxsbqrxgIDA1FTU4OCggI89thjfcbPmTMH69atQ1NTE8LDwzF+/Hi95VlZWThz5gzS09ORkZGBcePGQa1W4/r16zh16hTefPPNftf9w5zKysrw+9//Hk8//TQaGxuRl5cHT09PXL16VRcXHR2NiIgI/PGPf8Tt27cREhKC6upq/O1vfwOgf9RpzZo1mD9/Pl544QU8//zz8Pb2xp07d3Dt2jVUVFTo3RqAiB4OLIaIyCTWrFkDGxsb/OUvf8Hdu3cRHByM7du3Y+vWrX3GJycnY+PGjWhsbOzzcnRPT08cOHAAeXl5KCgowI0bNzBy5Eh4e3sjOjra4NRbX+bMmYPW1lZ8+OGHOHjwIMaOHYulS5eisbER77zzji7OysoKO3fuxKZNm7B79250d3cjIiICmzdvxrx58/TeKyAgAEVFRcjLy0Nubi7a2trg5OQEX19fzJgxYxB7jojMTSIIgmDuJIiILFFJSQlWrlyJ/fv3IyIiwtzpENEQ4ZEhIiIAhw8fxo0bNyCXy2FlZYXz58+joKAAkydPZiFE9IhjMUREBGDkyJE4cuQIduzYge+//x4eHh6YPXt2v1ezEdGjg6fJiIiISNR4B2oiIiISNRZDREREJGoshoiIiEjUWAwRERGRqLEYIiIiIlFjMURERESixmKIiIiIRI3FEBEREYna/wGKdz9rJ1pAeQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for sample_example in samples_list:\n",
    "    thr_significance = 0.05\n",
    "    title=samples_to_analyze_df.loc[samples_to_analyze_df['sample']==sample_example].iloc[0]['condition']\n",
    "    TSSs_of_interest = {'Junb;85705347':'Junb','JUNB;12791486':'JUNB'}\n",
    "    # TSSs_of_interest = {'Junb;85705347':'Junb','JUNB;12791486':'JUNB','Jun;94940459':'Jun','JUN;58784048':'JUN','Fos;85520664':'Fos','FOS;75278826':'FOS'}\n",
    "    \n",
    "    data = pivot[['TSS','chr','strand',sample_example+';average_log2',sample_example+';lfc',sample_example+';pval']]\n",
    "    data = data.rename(columns = {sample_example+';average_log2':'average_log2',sample_example+';lfc':'lfc',sample_example+';pval':'pval'})\n",
    "    data['FDR'] = multipletests(data['pval'],method = 'fdr_bh')[1]\n",
    "    data['sign'] = (data['FDR']<thr_significance).astype('str').str.replace('True','FDR<'+str(thr_significance)).replace('False','FDR>='+str(thr_significance)).astype('category')\n",
    "    \n",
    "    data_to_show = data.loc[data['TSS'].isin(TSSs_of_interest)].reset_index(drop=True)\n",
    "    \n",
    "    x_feature,y_feature,hue = 'average_log2','lfc','sign'\n",
    "    hue_order = ['FDR<'+str(thr_significance),'FDR>='+str(thr_significance)]\n",
    "    palette = ['pink','grey']\n",
    "    \n",
    "    sns.set(font_scale=1)\n",
    "    sns.set_style(\"white\")\n",
    "    fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3),)\n",
    "    \n",
    "    ax = sns.scatterplot(data = data,x=x_feature,y=y_feature,hue=hue,s=5,hue_order = hue_order,palette = palette,alpha=1)\n",
    "    ax = sns.scatterplot(data = data_to_show,x=x_feature,y=y_feature,hue=hue,s=20,edgecolor='black',linewidth=1,hue_order = hue_order,palette = palette,\n",
    "                         alpha=1,legend=None)\n",
    "    \n",
    "    for index, row in data_to_show.iterrows():\n",
    "        ax.text(row[x_feature]*0.95,row[y_feature],TSSs_of_interest[row['TSS']],ha='right',va='bottom',size=10)\n",
    "        \n",
    "    ax.set(xlabel = 'average',title=title)\n",
    "    ax.set_ylabel(ylabel=r'$log_2\\frac{expr[0,+150]}{expr[-150,0]}$',rotation=0,ha='right',va='center',rotation_mode='anchor')\n",
    "    ax.hlines(y=0,xmin=ax.get_xlim()[0],xmax=ax.get_xlim()[1],color='grey',linestyles='--',linewidth=0.7)\n",
    "\n",
    "    legend_labels = [elem+'\\n'+str(len(data.loc[data[hue]==elem]))+' TSS' for elem in hue_order]\n",
    "    h, l = ax.get_legend_handles_labels()\n",
    "    ax.legend(bbox_to_anchor=(1.001, 0.65),loc=2,borderaxespad=0.0,title='',markerscale=3,handles = h,labels = legend_labels)\n",
    "    \n",
    "    ax.tick_params(bottom=True,left=True)\n",
    "    \n",
    "    out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'bCLIP_quantification/', shell=True)\n",
    "    fig.savefig(subdirs['figures_dir']+'bCLIP_quantification/'+sample_example+'_MAplot.png',bbox_inches='tight',dpi=600)\n",
    "    fig.savefig(subdirs['figures_dir']+'bCLIP_quantification/'+sample_example+'_MAplot.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "86687451-2d34-4ecd-9db1-13cc0dfafc9f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mouse done\n",
      "human done\n"
     ]
    }
   ],
   "source": [
    "res = {}\n",
    "for organism in ['mouse','human']:\n",
    "    segments_of_interest = ['signal','control_up']\n",
    "    samples_list = list(samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism]['sample'])\n",
    "    \n",
    "    df = counts[organism]\n",
    "    df[samples_list] = df[samples_list].astype('int')\n",
    "    df['TSS'] = df.apply(lambda x:x['segment_name'].split(';')[-1]+';'+x['segment_name'].split(';')[1],1)\n",
    "    df['segment'] = df.apply(lambda x:x['segment_name'].split(';')[0],1).astype('category')\n",
    "    df = df.loc[df['segment'].isin(segments_of_interest)].reset_index(drop=True)\n",
    "    \n",
    "    pivot = pd.pivot_table(df,index=['TSS','chr','strand'],columns='segment',values = samples_list).reset_index()\n",
    "    columns = []\n",
    "    for elem in pivot.columns:\n",
    "        columns.append(';'.join(elem) if elem[1]!='' else elem[0])\n",
    "    pivot.columns = columns\n",
    "    \n",
    "    a = []\n",
    "    for sample in samples_list:\n",
    "        values = pivot[list(sample+';'+pd.Series(segments_of_interest))].drop_duplicates().reset_index(drop=True)\n",
    "        values.columns = segments_of_interest\n",
    "        a.append(values)\n",
    "    values = pd.concat(a).drop_duplicates().reset_index(drop=True)\n",
    "    values['sum'] = values[segments_of_interest].sum(1)\n",
    "    values['pval'] = values.apply(lambda x:stats.binomtest(k=x[segments_of_interest[0]],n=x['sum'],p=0.5,alternative='greater').pvalue if x['sum']>0 else 1,1)\n",
    "    values['lfc'] = np.log2((values[segments_of_interest[0]]+1)/(values[segments_of_interest[1]]+1))\n",
    "    values['average_log2'] = np.log2(values['sum']+1)\n",
    "    for sample in samples_list:\n",
    "        pivot = pd.merge(pivot,values.drop('sum',1).rename(columns={segments_of_interest[0]:sample+';'+segments_of_interest[0],\n",
    "                           segments_of_interest[1]:sample+';'+segments_of_interest[1],\n",
    "                          'pval':sample+';pval','lfc':sample+';lfc','average_log2':sample+';average_log2'}),how='left',on=[sample+';'+segments_of_interest[0],sample+';'+segments_of_interest[1]])\n",
    "    \n",
    "    thr_significance = 0.05\n",
    "    for sample in samples_list:\n",
    "        pivot[sample+';FDR'] = multipletests(pivot[sample+';pval'],method = 'fdr_bh')[1]\n",
    "        pivot[sample+';sign'] = (pivot[sample+';FDR']<thr_significance).astype('int')\n",
    "    pivot['gene_name'] = pivot.apply(lambda x:x['TSS'].split(';')[0].upper(),1)\n",
    "    pivot['coordinate'] = pivot['TSS'].str.split(';',expand=True)[1].astype('int')\n",
    "    res[organism] = pivot[['TSS','gene_name','coordinate','chr','strand']+list(pd.Series(samples_list)+';sign')]\n",
    "    print(organism+' done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "11db254d-2988-4a4a-ac26-e00c4caad409",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_bCLIP = res['mouse'].copy() # use downstream\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['tables_dir']+'bCLIP_quantification/', shell=True)\n",
    "data_bCLIP.to_csv(subdirs['tables_dir']+'bCLIP_quantification/'+'bCLIP.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "c638ffb6-6c07-4f0b-8f59-76867ce303f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_eCLIP = res['human'].copy() # use downstream\n",
    "for index,row in samples_to_analyze_df.iterrows():\n",
    "    if row['organism'] == 'human':\n",
    "        data_eCLIP = data_eCLIP.rename(columns={row['sample']+';sign':row['sample']+';'+row['condition']+';sign'})\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['tables_dir']+'bCLIP_quantification/', shell=True)\n",
    "data_eCLIP.to_csv(subdirs['tables_dir']+'bCLIP_quantification/'+'eCLIP.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "480afaef-baaa-4a66-ad62-ba96ac4fa28c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### look at proximal TSS only\n",
    "proximal_TSSs = {}\n",
    "for organism in ['mouse','human']:\n",
    "    df = res[organism][['gene_name','coordinate','strand']]\n",
    "    gr_plus = df.loc[df['strand']=='+'].groupby('gene_name').agg({'coordinate':np.min}).reset_index()\n",
    "    gr_minus = df.loc[df['strand']=='-'].groupby('gene_name').agg({'coordinate':np.max}).reset_index()\n",
    "    gr = pd.concat([gr_plus,gr_minus]).reset_index(drop=True)\n",
    "    proximal_TSS = pd.merge(res[organism].drop(['TSS','chr','strand'],1),gr,how='inner',on=['gene_name','coordinate']).drop(['coordinate'],1)\n",
    "    proximal_TSSs[organism] = proximal_TSS\n",
    "common_TSS = pd.merge(proximal_TSSs['human'],proximal_TSSs['mouse'],how='inner',on='gene_name')\n",
    "\n",
    "cols = list(common_TSS.columns[1:])\n",
    "cols = pd.DataFrame(cols)\n",
    "cols['sample'] = cols[0].str.split(';',expand=True)[0]\n",
    "common_TSS.columns = ['gene_name']+list(cols['sample'])\n",
    "\n",
    "cols = pd.merge(cols,samples_to_analyze_df,how='right',on='sample')\n",
    "cols = pd.merge(cols,plot_specification,how='right',on='condition')\n",
    "\n",
    "common_TSS = common_TSS[['gene_name']+list(cols['sample'])]\n",
    "\n",
    "from sklearn.metrics.pairwise import pairwise_distances\n",
    "A = 1 - pairwise_distances(common_TSS[list(cols['sample'])].T.to_numpy(), metric='jaccard')\n",
    "A = pd.DataFrame(A,columns = cols['condition'])\n",
    "A.index = cols['condition']\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3))\n",
    "\n",
    "ax = sns.heatmap(A,cbar_kws={'label': 'Jaccard similarity'},vmin=0,vmax=0.57,center=0,cmap=sns.color_palette('Spectral',as_cmap=True))\n",
    "ax.set(xlabel=\"\", ylabel=\"\")\n",
    "\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'bCLIP_quantification/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'bCLIP_quantification/'+'HeatMap.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'bCLIP_quantification/'+'HeatMap.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "bcf6e627-b505-4653-8623-054d3e3291d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "common_TSS_exp = common_TSS.copy()\n",
    "for index,row in samples_to_analyze_df.iterrows():\n",
    "    common_TSS_exp = common_TSS_exp.rename(columns={row['sample']:row['sample']+';'+row['condition']+';sign'})\n",
    "common_TSS_exp.to_csv(subdirs['tables_dir']+'bCLIP_quantification/'+'common_proximal_TSS.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30d369ed-9c14-4358-af75-717aa23fd273",
   "metadata": {},
   "source": [
    "# Compare bCLIP with PRO-seq"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bce793f3-8c73-45d0-95f0-d5c45c8266d7",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Metaplot for PRO-seq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "d98438cf-e4f5-4ef0-a6f9-5652f14fabae",
   "metadata": {},
   "outputs": [],
   "source": [
    "public_PROseq_samples = pd.read_csv(subdirs['metadata_dir']+'public_PROseq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "samples_to_analyze_df = public_PROseq_samples[['name','condition_name']]\n",
    "samples_to_analyze_df = samples_to_analyze_df.rename(columns={'name':'sample','condition_name':'condition'})\n",
    "\n",
    "experiments_to_analyze = ['SRR18735674','SRR18735676']\n",
    "samples_to_analyze_df = samples_to_analyze_df.loc[samples_to_analyze_df['sample'].isin(experiments_to_analyze)].reset_index(drop=True)\n",
    "\n",
    "plot_specification = samples_to_analyze_df[['condition']].drop_duplicates().reset_index(drop=True)\n",
    "plot_specification['color'] = ['orange','grey']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "d4436435-3559-4c06-93ca-071dd9803717",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6240624521659268"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "8154/(3470+438+493+511+8154)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "2129b15a-74ed-4a25-91bc-0e1df0293fd3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_feature,y_feature = 'pos_rel_to_TSS','mean'\n",
    "expr_cat = ''\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(5,2),)\n",
    "\n",
    "i=0\n",
    "title_dict = {'INTS11_degron':'Ints11 degron PROTAC','DMSO':'Ints11 degron DMSO'}\n",
    "for index,row in samples_to_analyze_df.iterrows():\n",
    "    sample = row['sample']\n",
    "    condition = row['condition']\n",
    "    title = title_dict[condition]\n",
    "    color = plot_specification.loc[plot_specification['condition']==condition].iloc[0]['color']\n",
    "    \n",
    "    file_path = subdirs['wf_output_dir']+'samples/'+sample+'/segment_counts_all/metaplot/'+sample+'.1.uniquely_mapped_0.metaplot_density.tsv'\n",
    "    tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "    l = list(tmp['expr_cat'].unique())\n",
    "    l.sort()\n",
    "    tmp = tmp.loc[tmp['expr_cat']==l[-1]].reset_index(drop=True)\n",
    "    ax = sns.lineplot(data = tmp,x=x_feature,y=y_feature,color=color,label=title)\n",
    "    \n",
    "    i=i+1\n",
    "ax.set(title='mean read density around\\ntop 60% TSS with highest expression',ylabel='',xlabel='position relative to TSS')\n",
    "ymin,ymax = ax.get_ylim()[0],ax.get_ylim()[1]\n",
    "ax.vlines(x=0,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.vlines(x=300,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.vlines(x=150,ymin=ymin,ymax=ymax,color='grey',linestyles='--',linewidth=0.7)\n",
    "ax.text(150,-0.0001,'+150',ha='center',va='center',size=10)\n",
    "ax.text(300,-0.0001,'+300',ha='left',va='center',size=10)\n",
    "ax.set(ylim=(-0.002,0.04))\n",
    "ax.legend(bbox_to_anchor=(0.01, 1),loc=2,borderaxespad=0.0,title='')\n",
    "\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'PROseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/Metaplots.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/Metaplots.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c502c20-bc06-4f87-8855-ddf707793f6b",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Quantification for PRO-seq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7c5937f2-f9f3-468f-9788-cd6a2e35d356",
   "metadata": {},
   "outputs": [],
   "source": [
    "public_PROseq_samples = pd.read_csv(subdirs['metadata_dir']+'public_PROseq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "samples_to_analyze_df = public_PROseq_samples[['name','condition_name']]\n",
    "samples_to_analyze_df = samples_to_analyze_df.rename(columns={'name':'sample','condition_name':'condition'})\n",
    "samples_to_analyze_df['organism'] = 'mouse'\n",
    "\n",
    "plot_specification = samples_to_analyze_df[['condition']].drop_duplicates().reset_index(drop=True)\n",
    "plot_specification['color'] = ['orange','grey']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "0914f0f8-867f-4d2b-b8a7-8e37105701e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "organisms = list(samples_to_analyze_df['organism'].unique())\n",
    "cl = []\n",
    "for organism in organisms:\n",
    "    enriched_gtf = pd.read_csv(file_paths[organism+'_enriched_annotation_file'],delimiter=\"\\t\",\n",
    "                                       index_col=None,header=None,usecols = [0])\n",
    "    chromosome_list =  list(enriched_gtf[0].unique())\n",
    "    cl.append([organism,' '.join(chromosome_list)])\n",
    "cl = pd.DataFrame(cl,columns=['organism','chromosomes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "473b4810-6c03-47f1-beaf-acb6ed30e80c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mouse, chr1 done\n",
      "mouse, chr2 done\n",
      "mouse, chr3 done\n",
      "mouse, chr4 done\n",
      "mouse, chr5 done\n",
      "mouse, chr6 done\n",
      "mouse, chr7 done\n",
      "mouse, chr8 done\n",
      "mouse, chr9 done\n",
      "mouse, chr10 done\n",
      "mouse, chr11 done\n",
      "mouse, chr12 done\n",
      "mouse, chr13 done\n",
      "mouse, chr14 done\n",
      "mouse, chr15 done\n",
      "mouse, chr16 done\n",
      "mouse, chr17 done\n",
      "mouse, chr18 done\n",
      "mouse, chr19 done\n",
      "mouse, chrX done\n",
      "mouse, chrY done\n",
      "mouse, chrM done\n"
     ]
    }
   ],
   "source": [
    "counts = {}\n",
    "for index1,row1 in cl.iterrows():\n",
    "    organism = row1['organism']\n",
    "    chromosomes = row1['chromosomes'].split(' ')\n",
    "    a1 = []\n",
    "    for chromosome in chromosomes:\n",
    "        i=0\n",
    "        a = []\n",
    "        for index,row in samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism].iterrows():\n",
    "            sample = row['sample']\n",
    "            file_path = subdirs['wf_output_dir']+'samples/'+sample+'/segment_counts_all/sel_TSSs/'+sample+'.'+chromosome+'.wd_counts.tsv'\n",
    "            if i==0:\n",
    "                tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,usecols = [0,3,4,5])\n",
    "            else:\n",
    "                tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,usecols=[5])\n",
    "            tmp = tmp.rename(columns = {'uniquely_mapped;0':sample})\n",
    "            a.append(tmp)\n",
    "            i=i+1\n",
    "        a = pd.concat(a,axis=1)\n",
    "        a1.append(a)\n",
    "        print(organism+', '+chromosome+' done')\n",
    "    a1 = pd.concat(a1).reset_index(drop=True)\n",
    "    a1[['chr','strand']] = a1[['chr','strand']].astype('category')\n",
    "    counts[organism] = a1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "bcdbff34-867b-4979-83d5-7c136a3298ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "organism = 'mouse'\n",
    "segments_of_interest = ['signal','control_down']\n",
    "samples_list = list(samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism]['sample'])\n",
    "condition_list = list(samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism]['condition'])\n",
    "\n",
    "df = counts[organism]\n",
    "df[samples_list] = df[samples_list].astype('int')\n",
    "\n",
    "df['TSS'] = df.apply(lambda x:x['segment_name'].split(';')[-1]+';'+x['segment_name'].split(';')[1],1)\n",
    "df['segment'] = df.apply(lambda x:x['segment_name'].split(';')[0],1).astype('category')\n",
    "df = df.loc[df['segment'].isin(segments_of_interest)].reset_index(drop=True)\n",
    "\n",
    "pivot = pd.pivot_table(df,index=['TSS','chr','strand'],columns='segment',values = samples_list).reset_index()\n",
    "columns = []\n",
    "for elem in pivot.columns:\n",
    "    columns.append(';'.join(elem) if elem[1]!='' else elem[0])\n",
    "pivot.columns = columns\n",
    "\n",
    "cols_for_fisher = []\n",
    "for condition in list(samples_to_analyze_df['condition'].unique()):\n",
    "    s = pd.Series(samples_to_analyze_df.loc[samples_to_analyze_df['condition']==condition]['sample'])\n",
    "    for segment in segments_of_interest:\n",
    "        pivot[condition+';'+segment] = pivot[list(s+';'+segment)].sum(1)\n",
    "        cols_for_fisher.append(condition+';'+segment)\n",
    "        \n",
    "values = pivot[cols_for_fisher].drop_duplicates().reset_index(drop=True)\n",
    "values['average_log2'] = np.log2(values[cols_for_fisher].mean(1))\n",
    "values[list(plot_specification['condition'])[0]+';ratio'] = (values[list(plot_specification['condition'])[0]+';'+segments_of_interest[1]]+1)/(values[list(plot_specification['condition'])[0]+';'+segments_of_interest[0]]+1)\n",
    "values[list(plot_specification['condition'])[1]+';ratio'] = (values[list(plot_specification['condition'])[1]+';'+segments_of_interest[1]]+1)/(values[list(plot_specification['condition'])[1]+';'+segments_of_interest[0]]+1)\n",
    "values['log2_OR'] = np.log2(values[list(plot_specification['condition'])[0]+';ratio']/values[list(plot_specification['condition'])[1]+';ratio'])\n",
    "values['pval'] = values.apply(lambda x:stats.fisher_exact([[x[list(plot_specification['condition'])[0]+';'+segments_of_interest[1]],x[list(plot_specification['condition'])[0]+';'+segments_of_interest[0]]],\n",
    "                                                           [x[list(plot_specification['condition'])[1]+';'+segments_of_interest[1]],x[list(plot_specification['condition'])[1]+';'+segments_of_interest[0]]]],\n",
    "                                                         alternative='two-sided')[1],1)\n",
    "pivot = pd.merge(pivot,values,how='left',on=cols_for_fisher)\n",
    "pivot['FDR'] = multipletests(pivot['pval'],method = 'fdr_bh')[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "69ab7e2f-78f5-4483-a230-4bded506d886",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "thr_significance = 0.05\n",
    "# TSSs_of_interest = {'Junb;85705347':'Junb','Fos;85520664':'Fos','FOS;75278826':'FOS','JUNB;12791486':'JUNB'}\n",
    "TSSs_of_interest = {'Junb;85705347':'Junb','JUNB;12791486':'JUNB'}\n",
    "\n",
    "data = pivot[['TSS','chr','strand','average_log2','log2_OR','pval','FDR']]\n",
    "data['sign'] = (data['pval']<thr_significance).astype('int')\n",
    "map_dict = {-1:'pval<'+str(thr_significance)+', $log_2OR<0$',1:'pval<'+str(thr_significance)+', $log_2OR>0$',0:'pval>='+str(thr_significance)}\n",
    "data['PROseq_cat'] = (data['sign']*((data['log2_OR']>0).astype('int')*2-1)).map(map_dict)\n",
    "\n",
    "data_to_show = data.loc[data['TSS'].isin(TSSs_of_interest)].reset_index(drop=True)\n",
    "\n",
    "x_feature,y_feature,hue = 'average_log2','log2_OR','PROseq_cat'\n",
    "hue_order = ['pval<'+str(thr_significance)+', $log_2OR>0$','pval>='+str(thr_significance),'pval<'+str(thr_significance)+', $log_2OR<0$']\n",
    "palette = ['orange','grey','purple']\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3),)\n",
    "\n",
    "ax = sns.scatterplot(data = data,x=x_feature,y=y_feature,hue=hue,s=3,hue_order = hue_order,palette = palette,alpha=1)\n",
    "ax = sns.scatterplot(data = data_to_show,x=x_feature,y=y_feature,hue=hue,s=20,edgecolor='black',linewidth=1,hue_order = hue_order,palette = palette,\n",
    "                     alpha=1,legend=None)\n",
    "\n",
    "for index, row in data_to_show.iterrows():\n",
    "    ax.text(row[x_feature]*0.95,row[y_feature]*1.2,TSSs_of_interest[row['TSS']],ha='center',va='bottom',size=10)\n",
    "    \n",
    "ax.set(xlabel = 'average, $log_2$',title='PRO-seq')\n",
    "ax.set_ylabel(ylabel=r'$log_2OR$',rotation=0,ha='right',va='center',rotation_mode='anchor')\n",
    "ax.hlines(y=0,xmin=ax.get_xlim()[0],xmax=ax.get_xlim()[1],color='grey',linestyles='--',linewidth=0.7)\n",
    "\n",
    "legend_labels = [elem+'\\n'+str(len(data.loc[data[hue]==elem]))+' TSS' for elem in hue_order]\n",
    "h, l = ax.get_legend_handles_labels()\n",
    "\n",
    "ax.legend(bbox_to_anchor=(1.001, 0.65),loc=2,borderaxespad=0.0,title='',markerscale=3,handles = h,labels = legend_labels)\n",
    "\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'PROseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/MA_plot.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/MA_plot.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8134c8d1-a2b2-46ef-bd70-f599b5926447",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_PROseq = data.copy()\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['tables_dir']+'PROseq_quantification/', shell=True)\n",
    "data_PROseq.to_csv(subdirs['tables_dir']+'PROseq_quantification/'+'PROseq.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "0f51377b-39f4-47d8-b370-2e24ecf32b52",
   "metadata": {},
   "outputs": [],
   "source": [
    "### Compare with bCLIP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "626ac94e-3991-4bca-8706-3d72e6576b46",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_bCLIP = pd.read_csv(subdirs['tables_dir']+'bCLIP_quantification/'+'bCLIP.tsv',delimiter=\"\\t\",index_col=None,header=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7ba36581-8c80-4f36-8484-7c72a860ae49",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_intersect = pd.merge(data_PROseq,data_bCLIP,how='inner',on=['TSS','chr','strand'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "id": "c2a2aae1-6548-471b-b54d-d517daa77a99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QUMCxY8cYNGhQift53OSmWuPGjePVV18lODiYCxcu8PHHHwP35/97Gr///nuJx3lYamoqAC4uLrqyH3/8EaDULliPHj3YtGkTP/74I23atOHkyZNERETw6quvEh4ejpWVFdeuXdNNPQX3v8iDBw/m+vXruolTL168yIoVK7hw4QKff/45ZmZmuolKT548yTvvvIOHhwcnTpxg1KhRjz3vx02+mpaWxvPPP0/v3r2xt7cnPT2djRs3EhwczDfffFPs85o+fTrdunXjo48+Qq1WU6NGDZYtW8bq1asZOHAgvXr14vr167z//vvk5+frJox4kvPdtGkTw4YNo0OHDrz99tsAumevyzJxrSFI8qvm/Pz8dIkA4KeffuL1119n9+7d/PTTT/Tt25fTp09z584d/P39S9zH4yY31QoODtZNyunv78+VK1f497//zfz588vUzSooKAAgOzubHTt2sGfPHjw8PPSSGvxvUsycnBx++OEHvvzySwIDA3Uxwv+mRn94hpkHad/T1j158iQajYbZs2frPdL1YIs4Pj6e8+fPk5CQoJuhxM/PjwYNGjB+/HgOHjxI165dOXToEEeOHGHGjBkMHToUuN/dtrS0ZNmyZaV+DnZ2dqVOvvrKK6/wyiuv6F4XFhbSrVs3OnbsyI4dO3TH0/Lz82POnDm617du3eKzzz7j1Vdf1St3c3Nj4MCBesmvrOfr7e2Nubk5devWLRZvWSauNQRJftWcn58fX3/9NVevXsXJyYmff/6ZN954g6ysLH744Qf69u3Ljz/+iEKh4MUXX3ymY5U0QWpubi4ZGRmPvamQk5Ojl7zMzMzo0qUL//znP4vV7dixo97r9u3bs3DhwqeOW5uYtV/uiRMn0r9/f1588cViEx/s378fNzc3WrdurUvWcH96KDMzM44ePUrXrl11d8W1k7FqBQYGPjb5Pc7du3eJjY3lP//5D2lpaXrrcpS0FOTDk8meOnWKvLy8YjMoe3t74+zsrFdW1vMtjYeHB9u3b2fJkiV07twZLy8vrK2ty3y+FUWSXzWnbc399NNPNGnShIKCAnx9ffnrr7+IjY3VvdeuXbtn/oV8eFLPJ5lGytramn/961+67ZydnXXdpod9/vnn2NnZcevWLRISEti9ezf//Oc/9Vox2plLUlNTcXV1LXE/2u6ydlLN9u3bExMTQ3x8PO+99x55eXm4ubkxduxY3Tq4GRkZXLlyRS9RP0g7wap2otKHJ0EoaWLXJzV58mQSExN5++238fDwwNbWFjMzM0aPHl3iBKoPH1Pb3axXr16xug//kSrr+ZbmcRPXGookv2quYcOGuLi48OOPP+Ls7EybNm2oXbs2fn5+zJ49m19++YVffvnlkbObVBZzc/MyT3SpVCp117U6duzIyJEjSUhIIDg4WG8djaVLl7Jnzx66dOlS4n60s5A82N3v2bMnPXv2JC8vj1OnTrF69WomT56Ms7Mzbdu2pU6dOlhZWTF//vwS96lNdtqJSjMzM/US4KPGI5bV7du3+f777wkPD2f06NG68ry8PG7dulXiNg9fctD+kXrwBpHWX3/9pdf6K+v5luZxE9caitztNQH+/v4kJiby448/6r7ozz//PI0bN2bFihXk5+c/duLMJ2nFVSYzMzNmzpyJhYUFn3zyia7cw8ODTp068e9//5uff/652HbHjx/n3//+N507d9bdLX6QQqHAx8dHNzYwOTkZuH+t6urVqzg4OJQ4war2OqJ2LOT27dv19lvWO5yP+ry1N1Menu7qq6++0uv+lsbLywuFQlFsCdBTp04Vu2Nc1vPVxvy434+SJq41FGn5mQA/Pz+++OILMjMzmT59uq7c19cXlUqFvb19iQngQaVNbmpoLi4uDBgwgC+++ILjx4/rhrYsWrSI4cOHM3LkSIYMGaJL8ImJiaxfvx5XV1e9a4WffPIJ169fx8/Pj4YNG5Kdnc369euxtLTEx8cHgGHDhvGf//yHwYMH89Zbb6FUKikqKuKPP/7g8OHDjBgxAi8vLzp16kT79u1ZvHgxarWaNm3acOLECbZt21amcypt8tX27dvz6aefUqdOHZydnTl69CibN2+mdu3aZdq3g4MDw4cPZ/Xq1dSuXVt3tzcmJgZHR0e9lmJZzxegZcuWHD16lH379uHo6IitrS2urq5lmrjWECT5mQBfX1/Mzc2xtrbWuxPn7++PSqWiQ4cOmJs/vhPwqMlNjUF4eDhbt25lxYoVupmk69evz6ZNm4iPj2fnzp26BZeaNWvGmDFjGDZsGDVr1tTtw8vLi6SkJJYsWcLNmzepXbs2bdq04fPPP9fdfa1ZsyYbNmxgzZo1bNq0idTUVKytrWnUqBH+/v66LqO5uTkrV65kwYIFxMXFkZ+fT7t27VizZk2ZlmosbfLVjz/+mHnz5rF48WIKCgpo164dn332GWPGjCnz5xUREYGNjQ1ffvklKpUKV1dXZs2axbJly/SSaFnPF2DGjBnMnj2bSZMmoVar8fHxIT4+vkwT1xqCTGYqRCVTKpWlziJtKFevXiUgIIDw8HCDJ6bKIC0/IUzQuXPn2LFjB23btsXOzo7ffvuNuLg47OzsdE+XVHeS/IQwQTY2NiQlJbF582Zu376NnZ0dHTp0YOLEiUY50UNFkG6vEMIkyVAXIYRJkuQnhDBJkvyEECZJbngYgZdeeom8vLxyee5TCFOXnp6OQqHg+PHjpdaT5GcEcnNzy/xokhCidAUFBZTlPq4kPyPg5OQE/O9B+8qmKSrEzNzCIMcWorz16NGjTPUk+RmR9O8nkp+VUqnHtHRogWO35ZV6TCGMgSQ/I5KflUJexllDhyGESZC7vUIIkyQtPxOUfqcGOXn3/+5ZFhZx58IFvfft7Ox0MyELUV1J8jMxt++ZE7m9KRqNds62XNgUplfH3NyczZs3Y29vX/kBClFJJPmZmFrWRSx47er/Wn72zan/0A0POzs7SXyi2pPkZ4Ic7f63CpeinjmNW7Y0YDRCGIYkPyNi6dDCJI4phDGQ5GdEDDXeTgY5C1P0xENdVCoVSqWSM2fOPNF2arWaqKgo3WLOT+rixYvMmjWLgQMH4u3tjVKpfOS+tm7dSkREBC+//DKtWrUqtpj2w86dO0dkZCTdu3fHw8ODtm3bEhQUxNq1a3VrnFZnkviEKaq0cX5qtZro6GiOHj36VNsnJSWxZ88e7O3t8fX1LbXutm3bSElJwdPTk2bNmpVaNyEhgf79+3PmzBlGjhxJXFwc0dHRvPLKK3z55ZfMmDHjqeIVQhi3KtPt7dOnD0FBQQDs2rWL/fv3P7Lup59+qluNbMyYMVy8eLHEeidPnmTWrFn4+/sTGxurtxZqx44dGT58OIcOHSrHsygfRUVFZVptTQjxaM+c/KZNm8bu3bvZunUrc+fO5fjx49SuXZuAgAAmTZqEQqEgNTVV97BxdHQ00dHRALqlD2/evMmyZcs4ePAgGRkZ2NnZ4eLiwvjx43WLbD/Jl72sdVevXo2ZmRn//Oc/iy0CDfcXYS7rQ9LlQaVSkZ6eXmodR0dH+vXrV0kRCVF9lUvLLz8/n7CwMIKDgxkxYgTHjh0jNjYWOzs7wsPDcXJyIi4ujtDQUIKDgwkJCQGgbt26AEydOpXk5GQiIiJwcXEhOzub5OTkCr3eVlhYSGJiIu7u7jRq1KjCjvMk0tPTuX79uqHDEMIklFvyGzdunG4xZj8/P5KSktixYwfh4eEoFArc3d0BaNiwod7C2QAnTpwgJCSEAQMG6Mp69uxZHqE9UmZmJmq1miZNmlTocSrCtWvXAOQRNCGeQbkkPzMzs2J3VJVKJYmJiWXa3tPTky1btuDg4IC/vz/u7u5YWlqWR2jVTm5uLsOGDQOQR9CEeAblkvxsbGywsrLSK1MoFOTm5pZp+2XLlrFy5Uo2b97MJ598Qs2aNenVqxdTp06tsKnd69Spg42NDampqRWy/4piZWXFunXrACTxCfEMjOKWYd26dZkxYwb79u1j//79TJ48me+++45p06ZV2DEtLCzw9fXl7NmzVe46W+PGjaXLK8QzqrTkp72beu/evVLrNW7cmMGDB+Pv709ycnKFxjRmzBg0Gg3vv/8+eXl5xd7Pz89n3759FRqDEMIwKm2cn52dHc7Ozuzduxc/Pz/s7e2pU6cO9vb2DB06lMDAQFxdXbG1teXMmTMcOnSIXr166bZXq9UcOHAAgF9++QWAY8eOkZmZiY2NDV27dtXVTUlJISXl/nTw6enpqNVqdu3aBUCLFi1o0eL+86xt27Zl1qxZzJ49m/79+zNo0CDc3NwoKCggOTmZhIQE3NzcHvuESHkpSxdfVngTonxU6iDnefPm8dFHHxEWFkZeXh5BQUHMmTMHT09Ptm3bRlpaGgUFBTRq1IhRo0YRGhqq2zYjI4MJEybo7S8qKgoAZ2dnvRbazp07dWMJtbTbhoeHM27cOF35gAED8PT05PPPPycuLo709HQsLS1xcXEhMDCQwYMHl/vn8ChlHb8ng5yFeHZmmrKs8SYqlHYgtaFWbxOiOinr90maDyagqLDI0CEIYXSqzLO9piB+dDw3zt8o1306KZ0YsmZIue5TiOpAkp8RuXH+Bqmnq9a4QyGqKun2CiFMkrT8qqlcRS6FFoXc4hYXHlqaEmR5SiEk+VVDBRYFnHc/D2aQQgo/hP1QrI4sTylMnSS/aqhGYQ2UZ5UUWhTSwK0Bg9cWH6soy1MKUyfJr5qyyrs/0YQ99rSUpSmFKEaSnxFxUjpViX0KUR1I8jMiFTUer6iwCHMLubEvxIMk+RmBtLQ0NBpNpa4XIkR1lZqaipmZ2WPrSfIzEk2aNJFne4UoBz169CAtLe2x9aQvZAScnZ0NHYIwAZqiQkOHUGnK8p2Slp8RSf9+IvlZKYYOQ1RDlg4tcOy23NBhGBVJfkYkPyuFvIyzhg5DCJMgyU+IaiL9Tg1y8kq+kmVZWMSdEh5z1DLFxx0l+QlRDdy+Z07k9qZoNI+6y5kLm8Ieub0pPu4oyU+IaqCWdRELXrv66JaffXPql3LNzxQfd5TkJ0Q14WhX8Mj3FPXMaSyPOeqRoS5CCJMkLT8jYunQwtAhiGpKfreKe+Lkp1KpiIyMZPPmzXh4eJR5O7VaTVxcHD4+PnTo0OFJD8vFixfZsGEDv/76K+fPn0etVrN+/foS97V161YOHDhAcnIyV65coXHjxqUuPn7u3DnWrVvHkSNHSE9Pp0aNGri4uPDqq68SEhKCg4PDE8f7NGQclqhImqJCzMwtDB2G0ai0bq9arSY6OpqjR48+1fZJSUns2bMHe3t7fH19S627bds2UlJS8PT0pFmzZqXWTUhIoH///pw5c4aRI0cSFxdHdHQ0r7zyCl9++SUzZsx4qniFMDaS+PRVmW5vnz59CAoKAmDXrl3s37//kXU//fRT3aLeY8aM4eLFiyXWO3nyJLNmzcLf35/Y2FgUCoXuvY4dOzJ8+HAOHTpUjmdRvcli6qIqeebkN23aNHbv3s3WrVuZO3cux48fp3bt2gQEBDBp0iQUCgWpqam6GUuio6OJjo4GICgoiIULF3Lz5k2WLVvGwYMHycjIwM7ODhcXF8aPH4+/vz/AE32pylp39erVmJmZ8c9//lMv8WkpFIpKnWlFpVKRnp5eaccrT46OjvTr18/QYQhRZuXS8svPzycsLIzg4GBGjBjBsWPHiI2Nxc7OjvDwcJycnIiLiyM0NJTg4GBCQkIAqFu3LgBTp04lOTmZiIgIXFxcyM7OJjk5maysrPIIr0SFhYUkJibi7u5Oo0aNKuw4TyI9PZ3r168bOgwhTEK5Jb9x48YREBAAgJ+fH0lJSezYsYPw8HAUCgXu7u4ANGzYEG9vb73tT5w4QUhICAMGDNCV9ezZszxCe6TMzEzUajVNmjSp0OMIIYxTuSQ/MzMzunfvrlemVCpJTEws0/aenp5s2bIFBwcH/P39cXd3x9LSsjxCE5VArVaTmZmpWyLTFJ8TFVVPuSQ/GxsbrKys9MoUCgW5ubll2n7ZsmWsXLmSzZs388knn1CzZk169erF1KlTcXR0LI8Qi6lTpw42NjakpqZWyP5NRX5+PseOHQPgu+++A0zzOVFR9RjF3d66desyY8YMZsyYwbVr19i3bx8ff/wxGRkZfPrppxVyTAsLC3x9fTl06BDXr1+nYcOGFXKc6s7S0pL27dvj4OCgu+Fhis+Jiqqn0sYlaO+m3rt3r9R6jRs3ZvDgwfj7+5OcnFyhMY0ZMwaNRsP7779PXl5esffz8/NLHRwt7rOxsaFOnTq0bNmSli1bSpdXVAmV1vKzs7PD2dmZvXv34ufnh729PXXq1MHe3p6hQ4cSGBiIq6srtra2nDlzhkOHDtGrVy/d9mq1mgMHDgDwyy+/AHDs2DEyMzOxsbGha9euuropKSmkpNyfETk9PR21Ws2uXbsAaNGiBS1a3H/Up23btsyaNYvZs2fTv39/Bg0ahJubGwUFBSQnJ5OQkICbm1ux65lCiKqvUru98+bN46OPPiIsLIy8vDyCgoKYM2cOnp6ebNu2jbS0NAoKCmjUqBGjRo0iNDRUt21GRgYTJkzQ219UVBRwf77+B1toO3fu1I0l1NJuGx4ezrhx43TlAwYMwNPTk88//5y4uDjS09OxtLTExcWFwMBABg8eXO6fw6NU1PXNylCVYxemyUyj0WgMHYSp0w6kruqrt8kTHsIYlPX7JL+potxI4hNVify2CpNSVFhk6BCEkTCKoS7ivvjR8dw4f8PQYVRbTkonhqwZYugwhJGQ5GdEbpy/QeppGXQtRGWQbq+olgosHr2eRWlu3bpVzpEIYyUtP1Ht5CpyOd/mPM0uN0OR+7+pym5xS/f8cUn++OMP5syZQ3x8vAzUNgGS/ES1U1ijEIDfXX/XK08hhR/Cfnjs9tnZ2ZL8TIAkP1Ht1MypSYtzLeChEawN3BoweG3pg9aLiopo1apVBUYnjIUkP1Et1cypWazMHntaytq14v9I8jMiTkonQ4dQrcnnKx4kj7cZgVatWqHRaGRWaSHKQWpqKmZmZpw7d67UetLyMxJNmjSp8s/2CmEMevToQVpa2mPryTg/I+Ds7GzoEEQZaYoKDR2CKIOyfKek5WdE0r+fSH5WiqHDEI9g6dACx27LDR2GKCeS/IxIflYKeRlnDR2GECZBur1CCJMkLT8hHpJ+pwY5ecXbBZaFRdwp5fE4WbKzapHkJ8QDbt8zJ3J7UzQasxLezYVNYY/cVpbsrFok+QnxgFrWRSx47WrJLT/75tQv5YaHLNlZtUjyE+IhjnYlT4elqGdOY3k8rtqQGx5CCJMkLT8jYunQwtAhiFLIz6d6eeLkp1KpiIyMZPPmzXh4eJR5O7VaTVxcHD4+PnTo0OFJD8vFixfZsGEDv/76K+fPn0etVrN+/fpH7uubb75hzZo1XL58GXt7ewICApg4cSK2trbFzkWhULBr165io8KHDBlCZmYmO3bseOJ4n4YMoDV+mqJCzMwtDB2GKAeV1u1Vq9VER0dz9OjRp9o+KSmJPXv2YG9vj6+vb6l1v/76ayZNmoSHhwdr164lPDycLVu26C1W/qC8vDyWL1/+VHEJ0yKJr/qoMt3ePn36EBQUBMCuXbvYv39/ifUKCwv56KOP6NSpE3PnzgXA19cXW1tbpkyZwoEDB+jataveNp07d2bHjh2MHDnSZCeylAXHhal55uQ3bdo0du/ezdatW5k7dy7Hjx+ndu3aBAQEMGnSJBQKBampqbpV1KOjo4mOjgYgKCiIhQsXcvPmTZYtW8bBgwfJyMjAzs4OFxcXxo8fj7+/P1D2BbFPnTpFeno6kZGReuWvvPIKM2fOZM+ePcWSX2hoKGfPnmXx4sV8+umnz/qRPDWVSkV6enqlH9fR0ZF+/fpV+nGFMKRyafnl5+cTFhZGcHAwI0aM4NixY8TGxmJnZ0d4eDhOTk7ExcURGhpKcHAwISEhANStWxeAqVOnkpycTEREBC4uLmRnZ5OcnExWVtYTx3Lx4kUAlEqlXrmlpSWurq669x9ka2tLWFgY8+bN46effsLPz++Jj1se0tPTuX79ukGOLYSpKbfkN27cOAICAgDw8/MjKSmJHTt2EB4ejkKhwN3dHYCGDRvi7e2tt/2JEycICQlhwIABurKePXs+VSzahFnSYFMHBwdSU0teF3fQoEGsX7+eJUuWsHnzZszMShrhL4SoLsrlIo+ZmRndu3fXK1MqlVy7dq1M23t6erJlyxZiY2M5deoU+fn55RLTk5QrFAomTpxIUlISO3fufObjVyV37tzhwoULZf55CVEdlEvys7GxwcrKSq9MoVCQm5tbpu2XLVtG37592bx5MwMHDsTHx4d33333qa5/OTg4AJTYZc7KytK9X5LevXvj7u7OsmXLyiUBVwX5+fns3LmTsLAwhg0bJot2C5NhFLf36taty4wZM9i3bx/79+9n8uTJfPfdd0ybNu2J96VdnevhxakLCgq4fPkybm5uj9zWzMyMKVOm8Pvvv5OQkPDEx66KLC0tCQgIYOXKlaxbt06eTRUmo9KSn0KhAODevXul1mvcuDGDBw/G39+f5OTkJz6Ol5cXjo6OqFQqvfLdu3eTk5NDr169St3e39+fjh07EhMTw927d5/4+FWRnZ0dLVu2lOmYhEmptHF+dnZ2ODs7s3fvXvz8/LC3t6dOnTrY29szdOhQAgMDcXV1xdbWljNnznDo0CG9RKVWqzlw4AAAv/zyCwDHjh0jMzMTGxsb3fAVCwsLpk6dyrvvvsvMmTPp3bs3V65cYfHixXTs2JEuXbo8NtYpU6bQr18/MjIySm0pljdHR8dKO5YxHFcIQ6rUQc7z5s3jo48+IiwsjLy8PIKCgpgzZw6enp5s27aNtLQ0CgoKaNSoEaNGjSI0NFS3bUZGBhMmTNDbX1RUFHB/sZJ9+/bpyvv06YOFhQVr1qxBpVLh4OBAnz59iIiIKFOcL7zwAr179660x9q0DDnWTgY5C1Mj6/YaAe0AcFm6UohnV9bvk/ypF0KYJEl+wuCKCosMHYIwQVVmYgNTED86nhvnbxg6jErlpHRiyJohhg5DmCBJfkbkxvkbpJ4u+fE7IUT5kuQnKkWuIpdCi8Ji5be4VWxAupYsBSkqkiQ/UeEKLAo4734eSnisOoUUfgj7ocTtZClIUZEk+YkKV6OwBsqzyhJbfg3cGjB47eASt5OlIEVFkuQnKoVVnlWJ5fbY657HFqIyyVAXIYRJkpafEXFSOhk6hEpniucsjIM83mYEWrVqhUajoUmTJoYORYgqLzU1FTMzM86dO1dqPWn5GYkmTZrIs71ClIMePXqQlpb22Hpyzc8IPLxYunh6mqLid5SF6SnLd0pafkYk/fuJ5GelGDqMKsvSoQWO3ZYbOgxRRUjyMyL5WSnkZZw1dBhCmATp9gohTJK0/ESVk36nBjl5xf9uWxYWcecRzwmDPCss9EnyE1XK7XvmRG5vikZT0vrLubAp7JHbyrPC4kGS/ESVUsu6iAWvXS255WffnPql3PCQZ4XFgyT5iSrH0a6gxHJFPXMay3PCoozkhocQwiRJy8+IWDq0MHQIVZp8fuJJPHHyU6lUREZGsnnzZjw8PMq8nVqtJi4uDh8fHzp06PCkh+XixYts2LCBX3/9lfPnz6NWq1m/fv0j9/XNN9+wZs0aLl++jL29PQEBAUycOBFbW9ti56JQKNi1a1exUeFDhgwhMzOz0tbvlQG6z05TVIiZuYWhwxBVQKV1e9VqNdHR0Rw9evSptk9KSmLPnj3Y29vj6+tbat2vv/6aSZMm4eHhwdq1awkPD2fLli2MGzeuxPp5eXksX778qeISxkUSnyirKtPt7dOnD0FBQQDs2rWL/fv3l1ivsLCQjz76iE6dOjF37lwAfH19sbW1ZcqUKRw4cICuXbvqbdO5c2d27NjByJEjadWqVcWeiAEVFRVhbi6XeYWAckh+06ZNY/fu3WzdupW5c+dy/PhxateuTUBAAJMmTUKhUJCamqpbRT06Opro6GgAgoKCWLhwITdv3mTZsmUcPHiQjIwM7OzscHFxYfz48fj7+wOU+Ut76tQp0tPTiYyM1Ct/5ZVXmDlzJnv27CmW/EJDQzl79iyLFy/m008/fdaP5KmpVCrS09MrZN+Ojo7069evQvYtRFVULi2//Px8wsLCCA4OZsSIERw7dozY2Fjs7OwIDw/HycmJuLg4QkNDCQ4OJiQkBIC6desCMHXqVJKTk4mIiMDFxYXs7GySk5PJysp64lguXrwIgFKp1Cu3tLTE1dVV9/6DbG1tCQsLY968efz000/4+fk98XHLQ3p6OtevXzfIsYUwNeWW/MaNG0dAQAAAfn5+JCUlsWPHDsLDw1EoFLi7uwPQsGFDvL299bY/ceIEISEhDBgwQFfWs2fPp4pFmzBLGszq4OBAamrJ6+IOGjSI9evXs2TJEjZv3oyZWUlPEFRdd+7c4cKFC/KIlxD/p1wuAJmZmdG9e3e9MqVSybVr18q0vaenJ1u2bCE2NpZTp06Rn59fLjE9SblCoWDixIkkJSWxc+fOZz6+McnPz2fnzp2EhYUxbNgwbt26ZeiQhDC4ckl+NjY2WFnpr86lUCjIzc0t0/bLli2jb9++bN68mYEDB+Lj48O77777VNe/HBwcAErsMmdlZeneL0nv3r1xd3dn2bJl5ZKAjYWlpSUBAQGsXLmSdevWySNeQmAkT3jUrVuXGTNmsG/fPvbv38/kyZP57rvvmDZt2hPvS7sM4oWHZvcoKCjg8uXLuLm5PXJbMzMzpkyZwu+//05CQsITH9uY2dnZ0bJlS+nyCvF/Ki35KRQKAO7du1dqvcaNGzN48GD8/f1JTk5+4uN4eXnh6OiISqXSK9+9ezc5OTn06tWr1O39/f3p2LEjMTEx3L1794mPL4SoGiptnJ+dnR3Ozs7s3bsXPz8/7O3tqVOnDvb29gwdOpTAwEBcXV2xtbXlzJkzHDp0SC9RqdVqDhw4AMAvv/wCwLFjx8jMzMTGxkY3fMXCwoKpU6fy7rvvMnPmTHr37s2VK1dYvHgxHTt2pEuXLo+NdcqUKfTr14+MjIxSW4rlzdHRsUruW4iqqFIHOc+bN4+PPvqIsLAw8vLyCAoKYs6cOXh6erJt2zbS0tIoKCigUaNGjBo1itDQUN22GRkZTJgwQW9/UVFRwP3FSvbt26cr79OnDxYWFqxZswaVSoWDgwN9+vQhIiKiTHG+8MIL9O7du9Iea9Oq6HF4MshZiP+RdXuNgHYAuCxdKcSzK+v3SZoB4pkVFRYZOgQhnliVebbXFMSPjufG+RuGDuOJOCmdGLJmiKHDEOKJSfIzIjfO3yD1dMlPoAghypd0e4UQJklafqLMchW5FFoU6pXd4laxAeUgy0QK4yfJT5RJgUUB593Pw0OPRqeQwg9hPxSrL8tECmMnyU+USY3CGijPKou1/Bq4NWDw2sHF6ssykcLYSfITZWaVZ1WszB573fPUQlQlcsNDCGGSpOVnRJyUToYO4YlVxZiFAHm8zSi0atUKjUZDkyZNDB2KEFVeamoqZmZmnDt3rtR60vIzEk2aNJFne4UoBz169CAtLe2x9eSanxF4eLF0TVHhI2oKIcri4e9USaTlZ0TSv58IgGO35QaNQwhTIMnPiORnpRg6BCFMhnR7hRAmSZKfEMIkSfITQpgkSX5CCJMkyU8IYZLkbq8RsXRoYegQhDAZkvyMiHZ8n6aoEDNzC8MGI0Q1V2WSn0qlIjIyUvfawsKCunXr0r59eyZMmICLi4vuvSFDhnD06FHd6xo1atCgQQN8fX155513Shz9vW/fPhISEjh9+jTZ2dnUrFmT1q1b079/fwICArC0tKzQ83uQJD4hKl6VSX5aCxYswNXVldzcXE6cOMGqVas4cuQIO3fu1Js8s2nTpixZsgSA/Px8Lly4QExMDD/++CM7d+7ExsYGAI1Gw/Tp01GpVHTt2pVp06bRqFEjbt++zZEjR5g9ezaZmZkMGzbMIOcrhKgYVS75ubm54eHhAUCHDh0oLCwkKiqKPXv20L9/f109a2trvL29da/bt2+PlZUVM2bM4Oeff6ZTp04AxMXFoVKpGDduHOHh4XrH6t69O6GhoVy5cqXiT+wBRUVFmJvLvSghKlKVS34P0ybCjIyMx9atVasWcL8bDPdbhHFxcbi6uvLOO++UuI2joyOOjo7lFG3pVCoVAP369auU4wlhyqp88ktNvb/O7YPX/LQKCgqA+0nu4sWLxMTE0LRpU9q1awdAUlISWVlZhISEYGZmVmz7ypaenm7oEIQwGVUu+RUVFVFQUKC75rdy5Urat29P9+7d9epdvHgRd3d3vTIXFxdWr16NQqEA4I8//gCQSUSFMEFVLvkNGDBA73Xz5s2JjY3VdWW1mjVrxtKlSwEoLCwkNTWVtWvX8tZbbxEfH19iS1EIYTqqXPJbtGgRzZs35+7du3z77bds2rSJSZMmERcXp1fPyspKdz0QwNvbGx8fH7p06cKKFStYunQpjRo1Av7XdRZCmI4qd0uxefPmeHh44Ovry5w5cwgJCeHQoUPs2rXrsds6OTlRp04d3dz+bdq0wcHBgb179yJLmQhhWqpc8nvY1KlTsbe3Z8WKFRQVFZVa9/r162RmZlKvXj0ALC0tCQ0N5fLly8TExJS4TUZGBj///HO5xy2EMKwq1+19mL29PaNHj2bx4sVs376dPn36AHDv3j1OnToF/O+an7Zr/OCAZW3yi4qK4syZMwQGBuoGOR87doyEhATGjRvHiy++WOHnUllDaoQQ1SD5wf3H2TZs2EBsbCyBgYEAXL16lYEDBwJgbm5O/fr1adWqFR988AE+Pj66bc3MzFiwYAE9e/YkISGB+fPnk52dja2tLa1atWLKlCmVNu5OexwZ5CxExZN1e41Ajx49AGTpSiHKQVm/T9K8MEJFhaVfuxRCPLtq0e2tLuJHxwMwZM0QA0ciRPUnyc+I3Dh/w9AhCGEypNsrhDBJkvyM0LVr17h27ZqhwxCiWpNur5HJI083DnHz5s16E7QKIcqPJD8jo0DBunXrACTxCVGBJPkZocaNGxs6BCGqPUl+RsRJ6WToEIQwGZL8jIh2fF9RYRHmFnIvSoiKJMnPCKSlpaHRaHSP5Qghnl5qamqZlqWQ5GckmjRpIs/2ClEOevToQVpa2mPrSd/KCDy8iLqmqNBAkQhRPTz8nSqJtPyMSPr3EwFw7LbcoHEIYQok+RmR/KwUQ4cghMmQbq8QwiRJ8hNCmCRJfkIIkyTJTwhhkiT5CSFMktztNSKWDi0MHYIQJqPKJD+VSkVkZKTutYWFBXXr1qV9+/ZMmDABFxcX3XtDhgzh6NGjutc1atSgQYMG+Pr68s4775Q4AHLfvn0kJCRw+vRpsrOzqVmzJq1bt6Z///4EBARgaWlZoecH/xvfpykqxMzcosKPJ4QpqzLJT2vBggW4urqSm5vLiRMnWLVqFUeOHGHnzp168981bdqUJUuWAJCfn8+FCxeIiYnhxx9/ZOfOndjY2ACg0WiYPn06KpWKrl27Mm3aNN2i5UeOHGH27NlkZmbqLXRe0STxCVHxqlzyc3Nzw8PDA4AOHTpQWFhIVFQUe/bsoX///rp61tbWeHt76163b98eKysrZsyYwc8//0ynTp0AiIuLQ6VSMW7cOMLDw/WO1b17d0JDQ7ly5UrFn9gDZNFyISpelUt+D9MmwoyMjMfWrVWrFnC/Gwz3W4RxcXG4urryzjvvlLiNo6Mjjo6O5RRt6VQqFQD9+vWrlOMJYcqqfPJLTU0F0Lvmp1VQUADcT3IXL14kJiaGpk2b0q5dOwCSkpLIysoiJCSkTFPgVLT09HRDhyCEyahyya+oqIiCggLdNb+VK1fSvn17unfvrlfv4sWLuLu765W5uLiwevVqFAoFAH/88QdwfzopIYRpqXLJb8CAAXqvmzdvTmxsrK4rq9WsWTOWLl0KQGFhIampqaxdu5a33nqL+Pj4EluKQgjTUeWS36JFi2jevDl3797l22+/ZdOmTUyaNIm4uDi9elZWVrrrgQDe3t74+PjQpUsXVqxYwdKlS2nUqBHwv66zEMJ0VLlbis2bN8fDwwNfX1/mzJlDSEgIhw4dYteuXY/d1snJiTp16nDu3DkA2rRpg4ODA3v37kWj0VR06EIII1Llkt/Dpk6dir29PStWrKCoqKjUutevXyczM5N69eoBYGlpSWhoKJcvXyYmJqbEbTIyMvj555/LPW4hhGFVuW7vw+zt7Rk9ejSLFy9m+/bt9OnTB4B79+5x6tQp4H/X/LRd4wcHLGuTX1RUFGfOnCEwMFA3yPnYsWMkJCQwbtw4XnzxxUo/NyFExanyyQ/uP862YcMGYmNjCQwMBODq1asMHDgQAHNzc+rXr0+rVq344IMP8PHx0W1rZmbGggUL6NmzJwkJCcyfP5/s7GxsbW1p1aoVU6ZMqbRxd5U1nlAIAWYaudhlcNolK7Wrt8kTHkI8vYe/T48i3zAjJIlPiIon3zIjVFRY+o0bIcSzqxbX/KqL+NHxAAxZM8TAkQhR/UnyMyI3zt8wdAhCmAzp9gohTJIkPyGESZLkJ4QwSZL8hBAmSZKfEMIkyd1eI+KkdDJ0CEKYDHm8zQh4eHhQWFiom19QCPH0/vjjDywsLDhz5kyp9aTlZwTy8/NNbj5B7RICppLwTe18wXDnXKNGDd1SFaXWq4RYxGNoF1F/3IPY1UlZHz6vLkztfMH4z1lueAghTJIkPyGESZLkJ4QwSZL8hBAmSZKfEMIkSfITQpgkGeQshDBJ0vITQpgkSX5CCJMkyU8IYZIk+QkhTJIkPyGESZLkJ4QwSZL8hBAmSZKfEMIkSfITQpgkSX5CCJMkyc+AfvvtN0aOHIm3tzd+fn7MnTuXe/fuGTqscrFz507efvttunbtire3N6+99hpffPEFRUVFevUOHDhA37598fDwoFevXmzYsMFAEZevu3fv0qVLF5RKZbG1JKrbOX/11Ve8/vrreHh44Ofnx9ixY/XeN9bzlWnsDSQ7O5thw4bRuHFjVqxYwc2bN1mwYAFZWVksWbLE0OE9s88++4zGjRvz7rvvUq9ePY4cOcK8efO4evUq7733HgAnT57k7bffpk+fPkybNo0TJ04wd+5cFAoFISEhBj6DZxMbG0thYWGx8up2zlFRUXz++eeMHTsWLy8vbt26xaFDh3TvG/X5aoRBrF69WuPl5aXJyMjQlX399deali1balJSUgwYWfl48Ly05s+fr/Hw8NDk5uZqNBqNZuTIkZrg4GC9Ou+//76mY8eOmsLCwkqJsyKkpKRovL29NRs3btS0bNlSc/r0ad171emcU1JSNK1bt9YcOnTokXWM+Xyl22sgBw8exM/Pj7p16+rKXn75ZRQKBQcOHDBgZOXjwfPSat26Nbm5uWRlZZGXl0diYiK9e/fWq/Paa6+Rnp5OcnJyZYVa7ubNm8egQYN4/vnn9cqr2zmrVCqaNm1Kp06dSnzf2M9Xkp+BXLp0iebNm+uVKRQKmjVrxqVLlwwUVcX6+eefcXBwoF69evz+++/k5+fj6uqqV6dFixYAVfYz2LVrF+fOneOdd94p9l51O+dffvmFli1bEhMTg5+fH23atGHw4MH8+uuvgPGfryQ/A8nOzqZ27drFymvXrs2tW7cMEFHFOnPmDCqVimHDhmFhYaE7x4c/A+3rqvgZqNVqFi5cyKRJk7Czsyv2fnU75/T0dA4fPsz27duZPXs2UVFRqNVqhg8fTnZ2ttGfr9zwMDIajQYzMzNDh1Gu0tPTGT9+PB4eHowaNUrvvUeda1X8DFauXEm9evXo169fqfWqyzlrNBpycnKIiorCzc0NAHd3d3r06MGmTZto164dYLznKy0/A6lduzbZ2dnFym/fvl1ii7Cqun37NqNGjcLa2pqVK1diaWkJgL29PVD8r7/2M6lqn0FaWhr/7//9P8aPH8+dO3fIzs4mJycHgJycHO7evVvtztne3p769evrEh+Ak5MTrq6upKSkGP35SvIzkObNmxe75pGXl8fvv/9e7FpgVZWbm0tYWBh//fUXcXFx1KlTR/des2bNsLS05PLly3rbpKSkAFS5zyA1NZX8/HxGjx5N+/btad++vW6829ChQxk+fHi1O+dHxavRaDA3Nzf685XkZyBdunQhMTGRzMxMXdl3331HXl4eXbt2NWBk5aOgoIAJEyZw7tw54uLicHZ21ntfoVDg6+vLzp079cp37NiBo6MjL7zwQmWG+8xat27N+vXr9f5FRkYCMHv2bD788MNqd87dunXjr7/+4sKFC7qyP//8k8uXL6NUKo3/fA060MaE3bp1S9O5c2fNoEGDNAcPHtRs2bJF06FDB83kyZMNHVq5+OCDDzQtW7bUrF27VnPy5Em9f7dv39ZoNBrNiRMnNC+88IJmxowZmsTERE1sbKymVatWmoSEBANHXz4SExOLjfOrTudcUFCgCQoK0vz973/XfPPNN5rvvvtO07dvX03nzp01d+/e1Wg0xn2+snqbAf3222/MnTuXn3/+GWtrawIDA5kyZQrW1taGDu2Zde/enbS0tBLfW79+PR06dADuP/q0dOlSLl26RMOGDRk+fDhvvvlmZYZaYY4cOcLQoUPZvHkzHh4euvLqdM4ZGRnMnz+fAwcOUFBQQPv27YmMjNQb3mKs5yvJTwhhkuSanxDCJEnyE0KYJEl+QgiTJMlPCGGSJPkJIUySJD8hhEmS5CeEMEmS/IQQJkmSnwn4448/GDVqFO3atSMgIIA9e/YUq7Nz5046dOjAzZs3y/34P/30E/369cPb2xulUlni8eH+ExFKpZJdu3aVed/Hjx9nwoQJdO7cmTZt2vDiiy8yaNAgvvjiC92sKnD/iZMxY8aUuq9p06bRtm1bvbIhQ4agVCp1/zw9PXn99df5/PPPiy3GVF4OHDhAVFRUhey7IqSkpBAVFUVqaqqhQ3kiMp+fCXjvvffIy8tjxYoVHD16lIkTJ/Ltt9/SrFkz4P60U/PmzePdd98tcfr5Z6HRaJg4cSIuLi6sXLkSGxubYtO7P60VK1YQExND27ZtmTBhAs2aNUOtVnPy5Emio6P573//y/Tp05/5OE2bNtUtKpWRkcGXX37JggULSE9PZ+rUqc+8/4cdOHCADRs2MG7cuHLfd0VISUkhOjoaHx8fmjRpYuhwykySXzWnVqs5evQoGzdupG3btnTq1Indu3fzww8/6JLf4sWLef755+nfv3+5H//GjRtkZWXRs2dP/Pz8ym2/O3fuJCYmhuDgYObOnas3MWbXrl0JDQ3l1KlT5XIsa2trvL29da+7dOlCQEAAGzZsYOLEibo5Ch+mVCpZsGDBYyc3rSxqtRobGxtDh2E0pNtbzeXn56PRaPR+6WvWrElubi4AJ06cYNu2bcyZM+eJ9338+HGGDRtG27Zt8fLyYtCgQXz//fe696OioujSpQsAS5YsQalU0r1798fuNzc3lwULFtCxY0c8PT0ZPHhwscVuYmNjsbe35/333y9xRmA7O7tHLqzzrCwtLXF3d0etVpf7ZYJp06bp1rV9sLut7VJu2LCBN998Ez8/P916yGvXriU/P19vP0OGDCEwMJBjx44xaNAgvLy8dK3g69evM378eNq2bctLL73E5MmTOX36NEqlEpVKpbefM2fOMHbsWHx8fPDw8KBv3758++23uvdVKhUTJkwA7s9bqI1Xu5/k5GTGjBmjW+OjU6dOjB49muvXr5fr5/Y0pOVXzdWuXRtXV1c+++wzpk+fzrFjxzh37hyzZ88mPz+fmTNnMnr06Cfuih49epQRI0bQsmVL5s2bh0KhYOPGjYwdO5alS5fy6quvEhISQqtWrQgPD9d9GRUKxWP3vWzZMl544QXmzp3L7du3iY6OZsiQIWzdupWmTZty48YNLly4wKuvvmqwlszVq1epUaOGbrbi8vL222+Tk5PD7t272bRpk67cyckJuL8oUGBgIE2aNMHS0pJz586xatUqLl++zIIFC/T2pe2Wh4aGEhERgbm5OTk5OQwdOpRbt24xZcoUnnvuOQ4dOkRERESxWBITEwkNDcXLy4tZs2ZRq1Ytvv32WyIiIrh37x79+vWjW7duTJo0iaVLlzJz5kzc3d2B+5PV5uTkMHz4cJo0acLMmTOpX78+6enpHDlyhLt375br5/Y0JPmZgHnz5jF+/Hh8fHwwNzcnLCwMT09PYmNj0Wg0xdbVKIuPP/6Y2rVrEx8fj62tLQB/+9vf6Nu3L4sWLSIgIICGDRtSUFAAQKNGjfS6jqWpW7cuMTExuhbdiy++yMsvv8zq1auZO3cuf/zxB0ClXl/SnsfNmzeJj4/n7NmzvPLKK7rpx4qKikq8AVJUVKTbFu6vW2FhYfHI4zRr1oz69esDlPh5aSdI1e77pZdewsHBgenTpzNt2jS9ZJyVlcXy5cv1Ljds2LCBK1eusHbtWl2rvFOnTqjVar1kC/cnYXVzc2PdunXUqHE/VXTu3JnMzEyWLl1K3759qVu3Ls899xxwf1W2B2NOSkoiKyuLefPm0bNnT135q6+++sjzr0yS/ExAu3bt2L9/P1evXsXR0ZFatWrx3//+l9WrV/Ppp59So0YNVqxYgUqlIj8/n5dffpn33nsPKyurEveXk5PDL7/8whtvvKFLfAAWFha8/vrrLFmyhMuXLz/1NOWBgYF6XVlnZ2fatm3LkSNHnmp/z+rixYu6Fg3c7/a+9tprfPjhh7qymJgYoqOji207Y8YMZsyYoXvt7OzMvn37njqW5ORkVqxYwcmTJ8nKytJ777///S9eXl661/b29sWusx47dgxbW1td4tMKDAzUS35Xrlzh8uXLvPfeewB6CbxLly7s37+f3377rdSf8XPPPYe9vT1LliwhPT2d9u3b65atNAaS/EyEpaWl3gSTH374IX369OGll17iq6++QqVS8fnnn1OzZk1CQ0NZvXo148ePL3Ff2dnZaDQaHB0di72n7Z49/MV8EtqWz8Nl586dA+63IoFKG1rRrFkzli5dipmZGVZWVjRp0qRYd3vAgAF069ZNryw4OJjw8HC98rJ0+x/l2rVrvPnmmzz//PNMnz4dZ2dnrKysOH36NHPmzOHevXt69Uv6+WRlZZX4+darV0/v9V9//QXAokWLWLRoUYnxPLgEQ0lq1apFfHw8q1atYtmyZdy6dQtHR0cGDBhAWFjYI28UVRZJfiZIpVJx6dIl3ViyQ4cO8corr+Di4gLc/9Ju27btkcmvdu3amJubk56eXuy9GzduAOgtVvSktF+8h8scHByA+wm2ZcuW/PDDD5VyB9PKykpvJuaSNGjQgAYNGhQrd3Z2fuy2ZbVnzx7dUpEPromi/aPwsJJuBDk4OHD69Oli5Q9/5tqf35gxY+jVq1eJ+y/LdWKlUsmyZcvQaDScP38elUpFTEwM1tbWjB49+rHbVyS522tibt68yaJFi5g+fbpu6UDN/62/qpWTk0NpE3zXrFkTLy8vvvvuO73WRlFREV9//TUNGzZ8prF8O3bs0Dt+WloaJ0+exMfHR1f29ttvc+vWLebOnVtirHfv3uXw4cNPHYMhaVuHD7fktMnswdajRqMhISGhzPtu3749d+/e5cCBA3rl33zzjd5rV1dXXFxcOHfuHB4eHiX+0y7M/qh4H469VatWut+7s2fPljnmiiItPxOzcOFCvLy89C46d+rUiYULF9K2bVtq1qxJfHw8wcHBpe5n0qRJjBgxgqFDhzJixAgsLS354osvuHjxoq6L+LRu3rzJO++8w4ABA7h9+zZRUVEoFAq9JzQCAgK4cOECsbGxXL58meDgYN0g59OnT/Pll1/y6quv6g13SU9PL/HpkfJsnZWHli1bAuhuSpibm6NUKvH398fS0pJJkyYRGhpKXl4eGzduLHH950cJCgpi3bp1vPvuu0yYMIHnnnuOgwcP6v5QmJv/rz00e/ZsRo0axciRIwkKCqJBgwbcunWLS5cucfbsWVasWAGgW7c3ISEBW1tb3aWBU6dO8cUXX9CzZ0+aNm2KRqPhP//5D9nZ2XTs2LG8Pq6nJsnPhPz0009899137NixQ688ODiYq1ev8vHHH5Ofn8/f//53wsLCSt2Xj48Pn3/+OVFRUURGRlJUVESrVq1YuXIlf/vb354pzoiICM6cOUNkZCR37tzB09OTpUuX6gZla02YMAF/f3/i4+NZtmwZWVlZWFlZ4ebmxvDhwxk4cKBe/bNnz+rGpD0oKCiIhQsXPlPM5SkwMJATJ07wxRdfEBMTg0ajYe/evTRv3pyoqCiWL1/OuHHjcHBwIDAwkLfeeqvMd+xr1qzJunXrmD9/PosXL8bMzIxOnTrx4YcfMnr0aGrVqqWr6+vry1dffcWqVauYP38+2dnZODg40Lx5cwICAnT1mjZtyvTp01m/fj1Dhw6lsLCQBQsW4O3tTe3atYmLi+PGjRtYWlry/PPPs3DhQoKCgsr9c3tSsoCREIJVq1axfPlyvv/+exo2bGjocCqFtPyEMDH/+te/gPvX9fLz80lMTCQ+Pp7XX3/dZBIfSPITwuRYW1uzbt06UlNTyc/Pp1GjRowaNeqxlzqqG+n2CiFMkgx1EUKYJEl+QgiTJMlPCGGSJPkJIUySJD8hhEmS5CeEMEmS/IQQJkmSnxDCJP1/Ohck1UGu7h4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 300x300 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = ['pval<'+str(thr_significance)+', $log_2OR>0$','pval>='+str(thr_significance),'pval<'+str(thr_significance)+', $log_2OR<0$']\n",
    "palette = ['orange','grey','purple']\n",
    "\n",
    "bclip_samples = ['Ints11C_replicate5','Ints11C_replicate6','Ints10N_replicate1','Ints10N_replicate2','RBC_exp17','RBC_exp18']\n",
    "\n",
    "def func1(x):\n",
    "    return 100*np.mean(x)+1\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(len(bclip_samples),1,sharey=True,sharex=True, figsize=(3,3))\n",
    "j=0\n",
    "for sample in bclip_samples:\n",
    "    ax = sns.barplot(ax=axes[j],data = data_intersect, orient='h',y=\"PROseq_cat\", x=sample+\";sign\", \n",
    "                     estimator=func1,palette = palette,order=order,capsize=0.001,errwidth=1)\n",
    "    ax.set_ylabel(ylabel=sample.split('_')[0],rotation=0,ha='right',va='center',rotation_mode='anchor')\n",
    "    ax.set(yticklabels=[],xlabel='',xlim=(0,70))\n",
    "    if j==0:\n",
    "        ax.set(title='Intersection of bCLIP\\nwith PROseq targets')\n",
    "    if j>0:\n",
    "        for spline in ['top']:\n",
    "            ax.spines[spline].set_visible(False)\n",
    "    j=j+1\n",
    "ax.tick_params(bottom=True)\n",
    "ax.set(xlabel = '% of bCLIP+ targets')\n",
    "fig.tight_layout(pad=0.001)\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'PROseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/Enrichment_bCLIP_ProSeq.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/Enrichment_bCLIP_ProSeq.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "cf9e5abb-6298-4bb8-bf9e-3591fed77fcc",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_intersect['11C+\\nAND\\n10N+'] = (data_intersect['Ints11C_replicate6;sign']+data_intersect['Ints10N_replicate1;sign']==2).astype('int')\n",
    "data_intersect['11C+\\nOR\\n10N+'] = (data_intersect['Ints11C_replicate6;sign']+data_intersect['Ints10N_replicate1;sign']>0).astype('int')\n",
    "data_intersect['11C+\\nAND\\n10N-'] = ((data_intersect['Ints11C_replicate6;sign']==1)&(data_intersect['Ints10N_replicate1;sign']==0)).astype('int')\n",
    "data_intersect['11C-\\nAND\\n10N+'] = ((data_intersect['Ints11C_replicate6;sign']==0)&(data_intersect['Ints10N_replicate1;sign']==1)).astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "id": "38949700-c4f0-4fd8-8d23-08f2f43bf30b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 400x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib_venn import venn3,venn3_circles\n",
    "from matplotlib_venn import venn2,venn2_circles\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(2, 1, sharey=False, sharex=False, figsize=(4,8))\n",
    "\n",
    "labels_of_interest = ['Ints11C_replicate6;sign','Ints10N_replicate1;sign']\n",
    "labels_to_show = ['Ints11C+','Ints10N+']\n",
    "i=0\n",
    "palette = ['orange','purple']\n",
    "for category in ['pval<'+str(thr_significance)+', $log_2OR>0$','pval<'+str(thr_significance)+', $log_2OR<0$']:\n",
    "    ax = sns.scatterplot(ax=axes[i],data = None)\n",
    "    ax.set(xlabel=category)\n",
    "\n",
    "    data = data_intersect.loc[data_intersect['PROseq_cat']==category].reset_index(drop=True)\n",
    "    \n",
    "    TSS_lists = []\n",
    "    for label in labels_of_interest:\n",
    "        TSS_list = set(list(data.loc[data[label]==1]['TSS'].astype('str')))\n",
    "        TSS_lists.append(TSS_list)\n",
    "    \n",
    "    v = venn2(TSS_lists,set_labels=labels_to_show,set_colors=[palette[i]]*3,ax=ax,alpha=1)\n",
    "    c = venn2_circles(TSS_lists,color='black',linewidth=1,ax=ax)\n",
    "    i=i+1\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'PROseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/Vienn_Diagram.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/Vienn_Diagram.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "f22bc569-0f94-4d87-8df7-a8e8efcb45b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 320x180 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = ['11C+\\nOR\\n10N+','11C+\\nAND\\n10N+','11C+\\nAND\\n10N-','11C-\\nAND\\n10N+']\n",
    "\n",
    "def func1(x):\n",
    "    return 100*np.mean(x)+1\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1,len(features),sharey=True,sharex=False, figsize=(0.8*len(features),1.8))\n",
    "\n",
    "j=0\n",
    "for feature in features:\n",
    "    ax = sns.barplot(ax=axes[j],data = data_intersect, x=\"PROseq_cat\", y=feature, estimator=func1,palette = palette,order=order,capsize=0.1,errwidth=1)\n",
    "    ax.set(xticks=[],title=feature,xlabel='',ylabel='',ylim=(0,60))\n",
    "    if j==0:\n",
    "        ax.set(ylabel='% of bCLIP+ TSS')\n",
    "        ax.tick_params(bottom=True,left=True)\n",
    "    if j>0:\n",
    "        for spline in ['left']:\n",
    "            ax.spines[spline].set_visible(False)\n",
    "    j=j+1\n",
    "fig.tight_layout(pad=0.001)\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'PROseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/Enrichment_bCLIP_ProSeq_union_intersection.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'PROseq/Enrichment_bCLIP_ProSeq_union_intersection.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b1e656f-ba27-448e-8571-0aa0c8664481",
   "metadata": {},
   "source": [
    "# Quantification for in-house and public RNA-seq"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71f1b131-0173-48c8-a9ac-26637cdc4101",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## get genic regions for FeatureCounts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "62635fba-6eae-42cb-8ced-e7121f79064a",
   "metadata": {},
   "outputs": [],
   "source": [
    "for organism in ['human','mouse']:\n",
    "    enriched_gtf = pd.read_csv(file_paths[organism+'_annotation_file'],delimiter=\"\\t\",index_col=None,header=None,skiprows=5)\n",
    "\n",
    "    ##########\n",
    "    # for DE analysis, quantify genes from exonic parts shared by all transcripts of the gene\n",
    "    ##########\n",
    "    \n",
    "    exons = enriched_gtf.loc[enriched_gtf[2]=='exon'].reset_index(drop=True)\n",
    "    exons['transcript_id'] = exons[8].str.split('transcript_id \"',expand=True)[1].str.split('\";',expand=True)[0]\n",
    "    exons['gene_id'] = exons[8].str.split('gene_id \"',expand=True)[1].str.split('\";',expand=True)[0]\n",
    "    exons['gene_name'] = exons[8].str.split('gene_name \"',expand=True)[1].str.split('\";',expand=True)[0]\n",
    "    exons['exon_number'] = exons[8].str.split('exon_number ',expand=True)[1].str.split(';',expand=True)[0].str.replace('\"','').astype('int')\n",
    "    exons['t']=1\n",
    "    exons = pd.merge(exons.drop('t',1),exons.groupby('transcript_id').agg({'t':sum}).reset_index(),how='inner',on='transcript_id')\n",
    "    \n",
    "    ####\n",
    "    # transform exons to bed format\n",
    "    ####\n",
    "    exons_bed = exons[[0,3,4,6,'transcript_id']].copy()\n",
    "    new_transcript_ids = exons_bed[['transcript_id']].drop_duplicates().reset_index(drop=True) # transform transcript ids to integers to save space\n",
    "    new_transcript_ids['new_transcript_id'] = new_transcript_ids.index\n",
    "    exons_bed = pd.merge(exons_bed,new_transcript_ids,how='left',on='transcript_id')\n",
    "    \n",
    "    exons_bed['name'] = exons_bed['new_transcript_id']\n",
    "    exons_bed['score'] = 0\n",
    "    exons_bed[3]=exons_bed[3]-1\n",
    "    exons_bed[[0,3,4,'name','score',6]].drop_duplicates().reset_index(drop=True).to_csv(subdirs['temp_dir']+'exons.bed', sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "    \n",
    "    command = 'bedtools sort -i '+subdirs['temp_dir']+'exons.bed'+' > '+subdirs['temp_dir']+'exons.sorted.bed'\n",
    "    out = subprocess.check_output(command, shell=True)\n",
    "    \n",
    "    ####\n",
    "    # get all unique exonic segments\n",
    "    ####\n",
    "    exons['start_True'] = True\n",
    "    exons['start_False'] = False\n",
    "    \n",
    "    a1 = []\n",
    "    a1 = a1 + [exons[[0,3,6,'start_True']].drop_duplicates().rename(columns={3:1,6:2,'start_True':3}),\n",
    "                        exons[[0,4,6,'start_False']].drop_duplicates().rename(columns={4:1,6:2,'start_False':3})]\n",
    "    \n",
    "    points = pd.concat(a1).sort_values([2,0,1,3]).drop_duplicates([0,1,2]).reset_index(drop=True) # prioritize element ends over starts if the coordinate matches exactly\n",
    "    \n",
    "    b = []\n",
    "    prev_chr,prev_coord,prev_str='',-1,''\n",
    "    for row in points.values:\n",
    "        if (row[0]==prev_chr and row[2]==prev_str):\n",
    "            b.append([row[0],prev_coord,(row[1]-1 if row[3] else row[1]),'n',0,row[2]])\n",
    "        prev_chr,prev_coord,prev_str = row[0],(row[1] if row[3] else row[1]+1),row[2]\n",
    "    segments = pd.DataFrame(b)\n",
    "    segments[1] = segments[1]-1\n",
    "    segments.to_csv(subdirs['temp_dir']+'exon_segments.bed', sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "    command = 'bedtools sort -i '+subdirs['temp_dir']+'exon_segments.bed'+' > '+subdirs['temp_dir']+'exon_segments.sorted.bed'\n",
    "    out = subprocess.check_output(command, shell=True)\n",
    "    \n",
    "    ###\n",
    "    # intersect exonic regions with exons to see which regions are overlapped by which exons\n",
    "    ###\n",
    "    \n",
    "    command = 'bedtools intersect -wa -wb -s -a '+subdirs['temp_dir']+'exon_segments.sorted.bed'+' -b '+subdirs['temp_dir']+'exons.sorted.bed | bedtools groupby -g 1,2,3,6 -c 10 -o distinct > '+subdirs['temp_dir']+'exon_segments.intersected_annotation.tsv'\n",
    "    out = subprocess.check_output(command, shell=True)\n",
    "    \n",
    "    exon_segments_intersected_annotation = pd.read_csv(subdirs['temp_dir']+'exon_segments.intersected_annotation.tsv',delimiter=\"\\t\",index_col=None,header=None)\n",
    "    \n",
    "    ###\n",
    "    # transform the comma-separated modifed transcript ids back to transcript ids and rename those with gene_ids in mind\n",
    "    ###\n",
    "    \n",
    "    unique_regions = list(exon_segments_intersected_annotation[4].unique())\n",
    "    num = len(unique_regions)\n",
    "\n",
    "    l = []\n",
    "    i=0\n",
    "    for elem in unique_regions:\n",
    "        l = l + [[elem,elem1] for elem1 in elem.split(',')]\n",
    "        if i%5000==0:\n",
    "            print(str(i)+' out of '+str(num)+' done')\n",
    "        i=i+1\n",
    "\n",
    "    l_df = pd.DataFrame(l,columns=[4,'new_transcript_id'])\n",
    "    l_df['new_transcript_id'] = l_df['new_transcript_id'].astype('int')\n",
    "    l_df = pd.merge(l_df,new_transcript_ids,how='left',on='new_transcript_id')\n",
    "    l_df = pd.merge(l_df,exons[['transcript_id','gene_id','gene_name']].drop_duplicates(),how='left',on='transcript_id')\n",
    "    l_df['t']=1\n",
    "    l_df.drop('t',axis=1).to_csv(subdirs[organism+'_annotation_dir']+('hg38_v42/' if organism=='human' else '')+'exonic_segments.explanation_of_gene_ids.tsv', sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE) # save the explanation if there will be a need to do \n",
    "\n",
    "    l_df = pd.read_csv(subdirs[organism+'_annotation_dir']+('hg38_v42/' if organism=='human' else '')+'exonic_segments.explanation_of_gene_ids.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "    l_df = l_df.rename(columns={'4':4})\n",
    "    l_df['t']=1\n",
    "    l_df_dedup = l_df.groupby([4,'gene_id','gene_name']).agg({'t':sum}).reset_index()\n",
    "    l_df_dedup['gene_ids'] = l_df_dedup[[4,'t','gene_id']].groupby([4,'t'])['gene_id'].transform(lambda x: ','.join(x))\n",
    "    l_df_dedup['gene_names'] = l_df_dedup[[4,'t','gene_name']].groupby([4,'t'])['gene_name'].transform(lambda x: ','.join(x))\n",
    "    l_df_dedup = l_df_dedup[[4,'t','gene_ids','gene_names']].drop_duplicates().reset_index(drop=True)\n",
    "    l_df_dedup = pd.merge(l_df_dedup,l_df_dedup.groupby('gene_ids').agg({'t':max}).rename(columns={'t':'t_max'}),how='left',on='gene_ids')\n",
    "\n",
    "    exon_segments_intersected_annotation = pd.merge(exon_segments_intersected_annotation,l_df_dedup,how='left',on=[4])\n",
    "    exon_segments_intersected_annotation['new_gene_id'] = exon_segments_intersected_annotation['gene_ids']+':'+exon_segments_intersected_annotation[4].astype('str')+':'+exon_segments_intersected_annotation['t'].astype('str')+':'+exon_segments_intersected_annotation['t_max'].astype('str')\n",
    "    exon_segments_intersected_annotation['new_gene_name'] = exon_segments_intersected_annotation['gene_names']+':'+exon_segments_intersected_annotation[4].astype('str')+':'+exon_segments_intersected_annotation['t'].astype('str')+':'+exon_segments_intersected_annotation['t_max'].astype('str')\n",
    "\n",
    "    # make gtf out of bed format\n",
    "    exon_segments_intersected_annotation_gtf = exon_segments_intersected_annotation.copy()\n",
    "    \n",
    "    a = []\n",
    "    for strand in ['+','-']:\n",
    "        if strand == '+':\n",
    "            tmp = exon_segments_intersected_annotation_gtf.loc[exon_segments_intersected_annotation_gtf[3]==strand].sort_values(['new_gene_id',1,2]).reset_index(drop=True)\n",
    "        else:\n",
    "            tmp = exon_segments_intersected_annotation_gtf.loc[exon_segments_intersected_annotation_gtf[3]==strand].sort_values(['new_gene_id',1,2],ascending=[True,False,False]).reset_index(drop=True)\n",
    "        tmp['e']=1\n",
    "        tmp['exon_number'] = tmp[['new_gene_id','e']].groupby(['new_gene_id']).cumsum()\n",
    "        a.append(tmp)\n",
    "    exon_segments_intersected_annotation_gtf = pd.concat(a).reset_index(drop=True)\n",
    "    \n",
    "    exon_segments_intersected_annotation_gtf[1] = exon_segments_intersected_annotation_gtf[1]+1\n",
    "    exon_segments_intersected_annotation_gtf = exon_segments_intersected_annotation_gtf.drop([4],axis=1).rename(columns={1:3,2:4,3:6})\n",
    "    exon_segments_intersected_annotation_gtf[1] = 'CUSTOM'\n",
    "    exon_segments_intersected_annotation_gtf[5] = '.'\n",
    "    exon_segments_intersected_annotation_gtf[7] = '.'\n",
    "    exon_segments_intersected_annotation_gtf[2] = 'exon'\n",
    "    exon_segments_intersected_annotation_gtf[8] = 'gene_id \"'+exon_segments_intersected_annotation_gtf['new_gene_id']+'\"; transcript_id \"'+exon_segments_intersected_annotation_gtf['new_gene_id']+':tr\";'+\\\n",
    "    ' gene_type \"NA\"; gene_name \"'+exon_segments_intersected_annotation_gtf['new_gene_name']+'\"; transcript_type \"NA\"; transcript_name \"'+exon_segments_intersected_annotation_gtf['new_gene_name']+':tr\"; '+\\\n",
    "    'exon_number '+exon_segments_intersected_annotation_gtf['exon_number'].astype('str')+'; exon_id \"'+exon_segments_intersected_annotation_gtf['new_gene_id']+':exon_'+exon_segments_intersected_annotation_gtf['exon_number'].astype('str')+'\"'\n",
    "    exon_segments_intersected_annotation_gtf['order'] = 3\n",
    "    exon_segments_intersected_annotation_gtf_exons = exon_segments_intersected_annotation_gtf[list(range(0,9))+['new_gene_id','order']].copy()\n",
    "    \n",
    "    exon_segments_intersected_annotation_gtf_transcripts = exon_segments_intersected_annotation_gtf.groupby([0,1,2,5,6,7,'new_gene_id','new_gene_name']).agg({3:min,4:max}).reset_index()\n",
    "    exon_segments_intersected_annotation_gtf_transcripts[2] = 'transcript'\n",
    "    exon_segments_intersected_annotation_gtf_transcripts[8] = 'gene_id \"'+exon_segments_intersected_annotation_gtf_transcripts['new_gene_id']+'\"; transcript_id \"'+exon_segments_intersected_annotation_gtf_transcripts['new_gene_id']+':tr\";'+\\\n",
    "    ' gene_type \"NA\"; gene_name \"'+exon_segments_intersected_annotation_gtf_transcripts['new_gene_name']+'\"; transcript_type \"NA\"; transcript_name \"'+exon_segments_intersected_annotation_gtf_transcripts['new_gene_name']+':tr\"'\n",
    "    exon_segments_intersected_annotation_gtf_transcripts['order'] = 2\n",
    "    exon_segments_intersected_annotation_gtf_transcripts = exon_segments_intersected_annotation_gtf_transcripts[list(range(0,9))+['new_gene_id','order']]\n",
    "    \n",
    "    exon_segments_intersected_annotation_gtf_genes = exon_segments_intersected_annotation_gtf.groupby([0,1,2,5,6,7,'new_gene_id','new_gene_name']).agg({3:min,4:max}).reset_index()\n",
    "    exon_segments_intersected_annotation_gtf_genes[2] = 'gene'\n",
    "    exon_segments_intersected_annotation_gtf_genes[8] = 'gene_id \"'+exon_segments_intersected_annotation_gtf_genes['new_gene_id']+'\"; gene_type \"NA\"; gene_name \"'+exon_segments_intersected_annotation_gtf_genes['new_gene_name']+'\"'\n",
    "    exon_segments_intersected_annotation_gtf_genes['order'] = 1\n",
    "    exon_segments_intersected_annotation_gtf_genes = exon_segments_intersected_annotation_gtf_genes[list(range(0,9))+['new_gene_id','order']]\n",
    "    \n",
    "    exon_segments_intersected_annotation_gtf = pd.concat([exon_segments_intersected_annotation_gtf_genes,exon_segments_intersected_annotation_gtf_transcripts,exon_segments_intersected_annotation_gtf_exons]).sort_values(['new_gene_id','order']).drop(['new_gene_id','order'],axis=1)\n",
    "    exon_segments_intersected_annotation_gtf = exon_segments_intersected_annotation_gtf.loc[exon_segments_intersected_annotation_gtf[3]<exon_segments_intersected_annotation_gtf[4]].reset_index(drop=True) # remove zero-length fragments\n",
    "    \n",
    "    exon_segments_intersected_annotation_gtf.to_csv(subdirs[organism+'_annotation_dir']+('hg38_v42/' if organism=='human' else '')+'exonic_segments.gtf', sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "\n",
    "    # make short gene ids for Feature Counts\n",
    "    exon_segments_intersected_annotation_gtf['gene_id'] = exon_segments_intersected_annotation_gtf[8].str.split('gene_id \"',expand=True)[1].str.split('\";',expand=True)[0]\n",
    "    tmp = exon_segments_intersected_annotation_gtf[['gene_id']].drop_duplicates().reset_index(drop=True)\n",
    "    tmp['short_gene_id'] = \"g\"+(tmp.index).astype('str')\n",
    "    if 'short_gene_id' in list(exon_segments_intersected_annotation_gtf.columns):\n",
    "        exon_segments_intersected_annotation_gtf = exon_segments_intersected_annotation_gtf.drop('short_gene_id',1)\n",
    "    exon_segments_intersected_annotation_gtf = pd.merge(exon_segments_intersected_annotation_gtf,tmp,how='left',on='gene_id')\n",
    "    exon_segments_intersected_annotation_gtf['8_new'] = exon_segments_intersected_annotation_gtf.apply(lambda x:x[8].replace(x['gene_id'],x['short_gene_id']),1)\n",
    "    \n",
    "    # save the explanation\n",
    "    exon_segments_intersected_annotation_gtf[[8,'8_new']].drop_duplicates().reset_index(drop=True).to_csv(subdirs[organism+'_annotation_dir']+('hg38_v42/' if organism=='human' else '')+'exonic_segments.explanation_of_short_gene_ids_feature_counts_.tsv', sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE) \n",
    "    \n",
    "    exon_segments_intersected_annotation_gtf[8] = exon_segments_intersected_annotation_gtf['8_new']\n",
    "    exon_segments_intersected_annotation_gtf = exon_segments_intersected_annotation_gtf.drop(['8_new','gene_id','short_gene_id'],1)\n",
    "    \n",
    "    exon_segments_intersected_annotation_gtf.to_csv(subdirs[organism+'_annotation_dir']+('hg38_v42/' if organism=='human' else '')+'exonic_segments.gtf', sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4795b213-3b9d-4b83-87da-4af5c7ba1e74",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Run FeatureCounts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2fc0e8b8-706a-44a5-9639-d1a39c037747",
   "metadata": {},
   "outputs": [],
   "source": [
    "exper_RNAseq_fastq_file_paths = pd.read_csv(subdirs['temp_dir']+\"\"\"exper_RNAseq_fastq_file_paths.tsv\"\"\",delimiter=\"\\t\",index_col=None,header=None)\n",
    "exper_RNAseq_fastq_file_paths.columns = ['path']\n",
    "exper_RNAseq_fastq_file_paths['name'] = exper_RNAseq_fastq_file_paths.apply(lambda x:x['path'].split('/')[-1][:-8],1)\n",
    "experimental_samples = exper_RNAseq_fastq_file_paths.drop_duplicates('name').reset_index(drop=True)\n",
    "experimental_samples['replicate'] = experimental_samples.apply(lambda x:x['name'].split('_')[0],1)\n",
    "\n",
    "mouse_replicates = ['A12','A13','A14','A15','A18','A19']\n",
    "human_replicates = list('A'+pd.Series(range(1,10)).astype('str'))\n",
    "\n",
    "experimental_samples = experimental_samples.loc[experimental_samples['replicate'].isin(human_replicates+mouse_replicates)].reset_index(drop=True).drop('path',1)\n",
    "\n",
    "condition_map = {'A12':'si_CTRL','A13':'si_Ints11','A14':'si_CTRL','A15':'si_Ints11','A18':'si_CTRL','A19':'si_Ints11',\n",
    "                'A1':'si_CTRL','A2':'si_INTS6','A3':'si_INTS6L','A4':'si_CTRL','A5':'si_INTS6','A6':'si_INTS6L','A7':'si_CTRL','A8':'si_INTS6','A9':'si_INTS6L'}\n",
    "\n",
    "experimental_samples['condition'] = experimental_samples['replicate'].map(condition_map)\n",
    "samples_to_analyze_df = experimental_samples[['name','condition','replicate']]\n",
    "samples_to_analyze_df['batch'] = 'in-house'\n",
    "samples_to_analyze_df['organism'] = samples_to_analyze_df.apply(lambda x:('human' if x['replicate'] in (human_replicates) else 'mouse'),1)\n",
    "samples_to_analyze_df = samples_to_analyze_df.drop('replicate',1)\n",
    "\n",
    "# public \n",
    "public_RNAseq_samples = pd.read_csv(subdirs['metadata_dir']+'public_RNAseq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "public_RNAseq_samples = public_RNAseq_samples.loc[public_RNAseq_samples['condition_name'].isin(['INTS11_si','siNT'])].reset_index(drop=True)\n",
    "condition_map = {'INTS11_si':'si_Ints11','siNT':'si_CTRL'}\n",
    "public_RNAseq_samples['condition'] = public_RNAseq_samples['condition_name'].map(condition_map)\n",
    "public_RNAseq_samples['batch'] = 'public'\n",
    "public_RNAseq_samples['organism'] = 'mouse'\n",
    "\n",
    "samples_to_analyze_df = pd.concat([samples_to_analyze_df,public_RNAseq_samples[['name','condition','batch','organism']]]).reset_index(drop=True)\n",
    "samples_to_analyze_df = samples_to_analyze_df.rename(columns = {'name':'sample'})\n",
    "\n",
    "plot_specification = samples_to_analyze_df[['condition']].drop_duplicates().reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "25eaff60-09b4-4327-8725-bd25f0a5edcf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A4_ZKRN240003206-1A_H735TDSXC_L3.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A4_ZKRN240003206-1A_H735TDSXC_L3/map_genome_all/A4_ZKRN240003206-1A_H735TDSXC_L3.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A7_ZKRN240003209-1A_H735TDSXC_L2.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A7_ZKRN240003209-1A_H735TDSXC_L2/map_genome_all/A7_ZKRN240003209-1A_H735TDSXC_L2.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A2_ZKRN240003204-1A_H735TDSXC_L3.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A2_ZKRN240003204-1A_H735TDSXC_L3/map_genome_all/A2_ZKRN240003204-1A_H735TDSXC_L3.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A6_ZKRN240003208-1A_H735TDSXC_L2.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A6_ZKRN240003208-1A_H735TDSXC_L2/map_genome_all/A6_ZKRN240003208-1A_H735TDSXC_L2.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A1_ZKRN240003203-1A_H735TDSXC_L3.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A1_ZKRN240003203-1A_H735TDSXC_L3/map_genome_all/A1_ZKRN240003203-1A_H735TDSXC_L3.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A9_ZKRN240003211-1A_H735TDSXC_L4.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A9_ZKRN240003211-1A_H735TDSXC_L4/map_genome_all/A9_ZKRN240003211-1A_H735TDSXC_L4.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A5_ZKRN240003207-1A_H5W23DSXC_L2.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A5_ZKRN240003207-1A_H5W23DSXC_L2/map_genome_all/A5_ZKRN240003207-1A_H5W23DSXC_L2.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A5_ZKRN240003207-1A_H735TDSXC_L2.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A5_ZKRN240003207-1A_H735TDSXC_L2/map_genome_all/A5_ZKRN240003207-1A_H735TDSXC_L2.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A8_ZKRN240003210-1A_H735TDSXC_L2.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A8_ZKRN240003210-1A_H735TDSXC_L2/map_genome_all/A8_ZKRN240003210-1A_H735TDSXC_L2.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A8_ZKRN240003210-1A_H5W23DSXC_L2.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A8_ZKRN240003210-1A_H5W23DSXC_L2/map_genome_all/A8_ZKRN240003210-1A_H5W23DSXC_L2.low_duplicate.bam && featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a /scicore/home/zavolan/GROUP/Genomes/homo_sapiens/hg38_v42/exonic_segments.gtf -o /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/gene_expression_quantification/human/FeatureCounts_exonic/A3_ZKRN240003205-1A_H735TDSXC_L3.exonic.txt /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/output/samples/A3_ZKRN240003205-1A_H735TDSXC_L3/map_genome_all/A3_ZKRN240003205-1A_H735TDSXC_L3.low_duplicate.bam && '"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "command = ''\n",
    "for organism in ['human','mouse']:\n",
    "    CDS_gtf = file_paths[organism+'_FeatureCounts_gtf_file']\n",
    "    outdir = os.path.join(subdirs['wf_output_dir'], \"gene_expression_quantification\", organism,\"FeatureCounts_exonic\")\n",
    "    out = subprocess.check_output('mkdir -p '+outdir, shell=True)\n",
    "\n",
    "    for index,row in samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism].iterrows():\n",
    "        sample = row['sample']    \n",
    "        bam=os.path.join(\n",
    "            subdirs['wf_output_dir'],\n",
    "            \"samples\",\n",
    "            sample,\n",
    "            \"map_genome_all\",\n",
    "            sample+\".low_duplicate.bam\")\n",
    "        output_file = outdir+'/'+sample+'.exonic.txt'  \n",
    "        command = command+'featureCounts -p -O --fraction -Q 255 -s 2 -B -C -P -d 0 -D 10000000000000 -T 8 -t exon -g gene_id -a '+CDS_gtf+' -o '+output_file+' '+bam+' && '\n",
    "command"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "5ab66c44-11c0-4667-9f41-c5ea4f03d99b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "human done\n"
     ]
    }
   ],
   "source": [
    "###\n",
    "# Select a set of features to use in the analysis\n",
    "###\n",
    "for organism in ['human','mouse']:\n",
    "\n",
    "    explanation_of_short_gene_ids_feature_counts_ = pd.read_csv(subdirs[organism+'_annotation_dir']+('hg38_v42/' if organism=='human' else '')+'exonic_segments.explanation_of_short_gene_ids_feature_counts_.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "    explanation_of_short_gene_ids_feature_counts_['gene_name'] = explanation_of_short_gene_ids_feature_counts_['8'].str.split('gene_name \"',expand=True)[1].str.split('\"',expand=True)[0]\n",
    "    explanation_of_short_gene_ids_feature_counts_['gene_id'] = explanation_of_short_gene_ids_feature_counts_['8'].str.split('gene_id \"',expand=True)[1].str.split('\"',expand=True)[0]\n",
    "    explanation_of_short_gene_ids_feature_counts_['short_gene_id'] = explanation_of_short_gene_ids_feature_counts_['8_new'].str.split('gene_id \"',expand=True)[1].str.split('\"',expand=True)[0]\n",
    "    explanation_of_short_gene_ids_feature_counts_ = explanation_of_short_gene_ids_feature_counts_[['short_gene_id','gene_name','gene_id']].drop_duplicates().reset_index(drop=True)\n",
    "\n",
    "    exonic_segments_gtf = pd.read_csv(subdirs[organism+'_annotation_dir']+('hg38_v42/' if organism=='human' else '')+'exonic_segments.gtf',delimiter=\"\\t\",index_col=None,header=None)\n",
    "    exonic_segments_genes = exonic_segments_gtf.loc[exonic_segments_gtf[2]=='gene'].reset_index(drop=True)\n",
    "    exonic_segments_genes['short_gene_id'] = exonic_segments_genes[8].str.split('gene_id \"',expand=True)[1].str.split('\"',expand=True)[0]\n",
    "    explanation_of_short_gene_ids_feature_counts_ = pd.merge(explanation_of_short_gene_ids_feature_counts_,exonic_segments_genes[['short_gene_id',0,3,4,6]],how='left',on='short_gene_id')\n",
    "    explanation_of_short_gene_ids_feature_counts_ = explanation_of_short_gene_ids_feature_counts_.rename(columns={0:'chr',3:'start',4:'end',6:'strand'})\n",
    "\n",
    "    # For each gene, we take the region having the maximum overlap of transcripts (e.g. 5:5 or 6:6). If there are several such regions for a gene (e.g. several regions with 5:5) - pool the raw counts for them.\n",
    "\n",
    "    explanation_of_short_gene_ids_feature_counts_ = pd.concat([explanation_of_short_gene_ids_feature_counts_,explanation_of_short_gene_ids_feature_counts_['gene_id'].str.split(':',expand=True)[[2,3]].rename(columns = {2:'num_cov',3:'max_cov'})],axis=1)\n",
    "    explanation_of_short_gene_ids_feature_counts_['actual_gene_id'] = explanation_of_short_gene_ids_feature_counts_['gene_id'].str.split(':',expand=True,n=1)[0]\n",
    "    explanation_of_short_gene_ids_feature_counts_['actual_gene_name'] = explanation_of_short_gene_ids_feature_counts_['gene_name'].str.split(':',expand=True,n=1)[0]\n",
    "\n",
    "    gr = explanation_of_short_gene_ids_feature_counts_.groupby('actual_gene_id').agg({'num_cov':max}).reset_index().rename(columns={'num_cov':'max_cov_alt'})\n",
    "    explanation_of_short_gene_ids_feature_counts_ = pd.merge(explanation_of_short_gene_ids_feature_counts_,gr,how='left',on='actual_gene_id')\n",
    "\n",
    "    sel_set_of_exonic_features = explanation_of_short_gene_ids_feature_counts_.loc[explanation_of_short_gene_ids_feature_counts_['num_cov']==explanation_of_short_gene_ids_feature_counts_['max_cov_alt']].drop(['num_cov','max_cov','actual_gene_id','actual_gene_name',\n",
    "                                                                                                                                                                                                                                 'max_cov_alt'],1)\n",
    "    sel_set_of_exonic_features = sel_set_of_exonic_features[['short_gene_id','chr','start','end','strand','gene_name','gene_id']].drop_duplicates().reset_index(drop=True)\n",
    "\n",
    "    out = subprocess.check_output('mkdir -p '+subdirs['tables_dir']+'gene_expression_RNA_seq/'+organism+'/', shell=True)\n",
    "\n",
    "    sel_set_of_exonic_features.to_csv(subdirs['tables_dir']+'gene_expression_RNA_seq/'+organism+'/sel_set_of_exonic_features.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)\n",
    "    print(organism+' done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "dd768b77-6ab7-41b2-8dbc-657f3189cb97",
   "metadata": {},
   "outputs": [],
   "source": [
    "###\n",
    "# make the gene expression matrix for RNA-seq samples in different organisms\n",
    "###\n",
    "\n",
    "for organism in ['human','mouse']:\n",
    "    samples_list = list(samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism]['sample'])\n",
    "    sel_set_of_exonic_features = pd.read_csv(subdirs['tables_dir']+'gene_expression_RNA_seq/'+organism+'/sel_set_of_exonic_features.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "    sel_set_of_exonic_features['actual_gene_id'] = sel_set_of_exonic_features['gene_id'].str.split(':',expand=True,n=1)[0]\n",
    "    \n",
    "    i=0\n",
    "    for sample in samples_list:\n",
    "        file_path = subdirs['wf_output_dir']+'gene_expression_quantification/'+organism+'/FeatureCounts_exonic/'+sample+'.exonic.txt'\n",
    "        tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,skiprows=1,usecols=[0,6])\n",
    "        tmp.columns = ['short_gene_id',sample]\n",
    "        if i==0:\n",
    "            res = tmp.copy()\n",
    "        else:\n",
    "            res = pd.merge(res,tmp,how='outer',on='short_gene_id')\n",
    "        i=i+1\n",
    "    res = pd.merge(sel_set_of_exonic_features[['short_gene_id','actual_gene_id']],res,how='left',on='short_gene_id').drop('short_gene_id',1)\n",
    "    # pool over actual gene ids\n",
    "    res = res.groupby('actual_gene_id').sum()\n",
    "    res['actual_gene_id'] = res.index\n",
    "    res = res.reset_index(drop=True)[['actual_gene_id']+samples_list]\n",
    "\n",
    "    res[samples_list] = res[samples_list].fillna(0).astype('int')\n",
    "    out = subprocess.check_output('mkdir -p '+subdirs['tables_dir']+'gene_expression_RNA_seq/'+organism+'/', shell=True)\n",
    "    res.to_csv(subdirs['tables_dir']+'gene_expression_RNA_seq/'+organism+'/exonic.FeatureCounts.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40ab7678-ad17-437d-862b-f85ef1e0d22c",
   "metadata": {},
   "source": [
    "## Run DESEQ2 comparisons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "249afb92-752e-4f41-a326-b6d61fcfb6e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "exper_RNAseq_fastq_file_paths = pd.read_csv(subdirs['temp_dir']+\"\"\"exper_RNAseq_fastq_file_paths.tsv\"\"\",delimiter=\"\\t\",index_col=None,header=None)\n",
    "exper_RNAseq_fastq_file_paths.columns = ['path']\n",
    "exper_RNAseq_fastq_file_paths['name'] = exper_RNAseq_fastq_file_paths.apply(lambda x:x['path'].split('/')[-1][:-8],1)\n",
    "experimental_samples = exper_RNAseq_fastq_file_paths.drop_duplicates('name').reset_index(drop=True)\n",
    "experimental_samples['replicate'] = experimental_samples.apply(lambda x:x['name'].split('_')[0],1)\n",
    "\n",
    "mouse_replicates = ['A12','A13','A14','A15','A18','A19']\n",
    "human_replicates = list('A'+pd.Series(range(1,10)).astype('str'))\n",
    "\n",
    "experimental_samples = experimental_samples.loc[experimental_samples['replicate'].isin(human_replicates+mouse_replicates)].reset_index(drop=True).drop('path',1)\n",
    "\n",
    "condition_map = {'A12':'si_CTRL','A13':'si_Ints11','A14':'si_CTRL','A15':'si_Ints11','A18':'si_CTRL','A19':'si_Ints11',\n",
    "                'A1':'si_CTRL','A2':'si_INTS6','A3':'si_INTS6L','A4':'si_CTRL','A5':'si_INTS6','A6':'si_INTS6L','A7':'si_CTRL','A8':'si_INTS6','A9':'si_INTS6L'}\n",
    "\n",
    "experimental_samples['condition'] = experimental_samples['replicate'].map(condition_map)\n",
    "experimental_samples['organism'] = experimental_samples.apply(lambda x:('human' if x['replicate'] in human_replicates else 'mouse'),1)\n",
    "samples_to_analyze_df = experimental_samples[['name','condition','organism']]\n",
    "samples_to_analyze_df['batch'] = 'in-house'\n",
    "\n",
    "\n",
    "# public \n",
    "public_RNAseq_samples = pd.read_csv(subdirs['metadata_dir']+'public_RNAseq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "public_RNAseq_samples = public_RNAseq_samples.loc[public_RNAseq_samples['condition_name'].isin(['INTS11_si','siNT'])].reset_index(drop=True)\n",
    "condition_map = {'INTS11_si':'si_Ints11','siNT':'si_CTRL'}\n",
    "public_RNAseq_samples['condition'] = public_RNAseq_samples['condition_name'].map(condition_map)\n",
    "public_RNAseq_samples['organism'] = 'mouse'\n",
    "public_RNAseq_samples['batch'] = 'public'\n",
    "\n",
    "samples_to_analyze_df = pd.concat([samples_to_analyze_df[['name','condition','batch','organism']],public_RNAseq_samples[['name','condition','batch','organism']]]).reset_index(drop=True)\n",
    "samples_to_analyze_df = samples_to_analyze_df.rename(columns = {'name':'sample'})\n",
    "\n",
    "plot_specification = samples_to_analyze_df[['condition']].drop_duplicates().reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f8517da9-138d-4da6-b520-9ae0b6b9f31c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rscript /scicore/home/zavolan/mirono0000/Projects/bCLIP/bclip_workflow/scripts/run_deseq2.r /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_human_in-house_si_INTS6_vs_si_CTRL/counts.tsv /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_human_in-house_si_INTS6_vs_si_CTRL/metadata.tsv si_INTS6 /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_human_in-house_si_INTS6_vs_si_CTRL/ fake_gene & Rscript /scicore/home/zavolan/mirono0000/Projects/bCLIP/bclip_workflow/scripts/run_deseq2.r /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_human_in-house_si_INTS6L_vs_si_CTRL/counts.tsv /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_human_in-house_si_INTS6L_vs_si_CTRL/metadata.tsv si_INTS6L /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_human_in-house_si_INTS6L_vs_si_CTRL/ fake_gene & Rscript /scicore/home/zavolan/mirono0000/Projects/bCLIP/bclip_workflow/scripts/run_deseq2.r /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_mouse_in-house_si_Ints11_vs_si_CTRL/counts.tsv /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_mouse_in-house_si_Ints11_vs_si_CTRL/metadata.tsv si_Ints11 /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_mouse_in-house_si_Ints11_vs_si_CTRL/ fake_gene & Rscript /scicore/home/zavolan/mirono0000/Projects/bCLIP/bclip_workflow/scripts/run_deseq2.r /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_mouse_public_si_Ints11_vs_si_CTRL/counts.tsv /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_mouse_public_si_Ints11_vs_si_CTRL/metadata.tsv si_Ints11 /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_mouse_public_si_Ints11_vs_si_CTRL/ fake_gene & \n"
     ]
    }
   ],
   "source": [
    "res_dict = {}\n",
    "big_command = ''\n",
    "for organism in ['human','mouse']:\n",
    "    df = pd.read_csv(subdirs['tables_dir']+'gene_expression_RNA_seq/'+organism+'/exonic.FeatureCounts.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "    for batch in list(samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism]['batch'].unique()):\n",
    "        metadata_df = samples_to_analyze_df.loc[(samples_to_analyze_df['batch']==batch)&(samples_to_analyze_df['organism']==organism)].reset_index(drop=True)\n",
    "        conditions = (metadata_df['condition'].unique())\n",
    "        condition_2 = 'si_CTRL'\n",
    "        for condition_1 in [elem for elem in conditions if elem!=condition_2]:\n",
    "            metadata_df_cur = metadata_df.loc[metadata_df['condition'].isin([condition_1,condition_2])].reset_index(drop=True)\n",
    "            counts_df = df[['actual_gene_id']+list(metadata_df_cur['sample'])]\n",
    "\n",
    "            outdir_path = subdirs['tables_dir']+'Deseq2/RNAseq_'+organism+'_'+batch+'_'+condition_1+'_vs_'+condition_2+'/'\n",
    "            count_file_path = outdir_path+'counts.tsv'\n",
    "            metadata_file_path = outdir_path+'metadata.tsv'            \n",
    "\n",
    "            out = subprocess.check_output('mkdir -p '+outdir_path, shell=True)\n",
    "            \n",
    "            metadata_df_cur[['sample','condition']].to_csv(metadata_file_path,sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)\n",
    "            counts_df.to_csv(count_file_path,sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)\n",
    "            command = \\\n",
    "            \"\"\"Rscript \"\"\"+subdirs['wf_dir']+'scripts/run_deseq2.r'+' '+count_file_path+' '+metadata_file_path+' '+condition_1+' '+outdir_path+' fake_gene & '\n",
    "            big_command = big_command + command\n",
    "            res_dict[organism+';'+batch+';'+condition_1+'_vs_'+condition_2] = outdir_path+'DE_table.tsv'\n",
    "print(big_command)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7d8ea7b2-caa5-415d-99fd-361934365790",
   "metadata": {},
   "outputs": [],
   "source": [
    "genes_dict = {}\n",
    "for organism in ['human','mouse']:\n",
    "    enriched_gtf = pd.read_csv(file_paths[organism+'_annotation_file'],delimiter=\"\\t\",index_col=None,header=None,skiprows=5)\n",
    "    genes = enriched_gtf.loc[enriched_gtf[2]=='gene'].reset_index(drop=True)\n",
    "    genes['gene_id'] = genes[8].str.split('gene_id \"',expand=True)[1].str.split('\";',expand=True)[0]\n",
    "    genes['gene_name'] = genes[8].str.split('gene_name \"',expand=True)[1].str.split('\";',expand=True)[0]\n",
    "    genes['gene_type'] = genes[8].str.split('gene_type \"',expand=True)[1].str.split('\";',expand=True)[0]\n",
    "    genes = genes[['gene_id','gene_name','gene_type']].drop_duplicates().reset_index(drop=True)\n",
    "    genes_dict[organism] = genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b880077e-cad8-4c5f-8d2a-f97c2e647dcd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ensure concordance with Ints13 for human\n",
    "DE_table_Ints13 = pd.read_csv(subdirs['tables_dir']+'Deseq2/results_DESeq_ints13_Depletion_vs_negctrl.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "DE_table_Ints13.loc[~DE_table_Ints13['log2FoldChange'].isna()].reset_index(drop=True)\n",
    "used_genes = list(DE_table_Ints13['ID'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e69cb4e1-3a44-4942-861d-9a014a46fc1b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "DE_dict = {}\n",
    "for DE_analysis in res_dict:\n",
    "    organism,batch,comparison = DE_analysis.split(';')\n",
    "    targeted_gene_name = comparison.split('_vs_')[0].replace('si_','')\n",
    "\n",
    "    genes_of_interest = {targeted_gene_name:targeted_gene_name,'JUNB':'JUNB','Junb':'Junb'}\n",
    "    # genes_of_interest = {targeted_gene_name:targeted_gene_name}\n",
    "    \n",
    "    thr_significance = 0.05\n",
    "    significance_feature = 'FDR'\n",
    "    DE_table = pd.read_csv(res_dict[DE_analysis],delimiter=\"\\t\",index_col=None,header=0)\n",
    "    DE_table = DE_table.rename(columns = {'gene_name':'gene_id'})\n",
    "    DE_table = pd.merge(genes_dict[organism],DE_table,how='right',on='gene_id')\n",
    "    # if human, intersect with Ints13\n",
    "    if organism=='human':\n",
    "        DE_table['ID'] = DE_table['gene_id'].str.split('.',expand=True)[0]\n",
    "        DE_table = DE_table.loc[DE_table['ID'].isin(used_genes)].sort_values('gene_id').drop_duplicates('ID').drop('ID',1).reset_index(drop=True)\n",
    "    \n",
    "    # look only at protein-coding\n",
    "    DE_table = DE_table.loc[DE_table['gene_type']=='protein_coding'].reset_index(drop=True)\n",
    "    \n",
    "    DE_table['log2FoldChange'] = DE_table['log2FoldChange'].fillna(0)\n",
    "    DE_table[['pvalue','padj']] = DE_table[['pvalue','padj']].fillna(1)\n",
    "    DE_table['FDR'] = multipletests(DE_table['pvalue'],method = 'fdr_bh')[1]\n",
    "    DE_table['sign'] = (DE_table[significance_feature]<thr_significance).astype('int')\n",
    "    map_dict = {-1:significance_feature+'<'+str(thr_significance)+', $log_2FC<0$',1:significance_feature+'<'+str(thr_significance)+', $log_2FC>0$',0:significance_feature+'>='+str(thr_significance)}\n",
    "    DE_table['RNAseq_cat'] = (DE_table['sign']*((DE_table['log2FoldChange']>0).astype('int')*2-1)).map(map_dict)\n",
    "    DE_table['log2_mean'] = np.log2(DE_table['baseMean'])\n",
    "    \n",
    "\n",
    "    data = DE_table.copy()\n",
    "    data_to_show = data.loc[data['gene_name'].isin(genes_of_interest)].reset_index(drop=True)\n",
    "    \n",
    "    x_feature,y_feature,hue = 'log2_mean','log2FoldChange','RNAseq_cat'\n",
    "    hue_order = [significance_feature+'<'+str(thr_significance)+', $log_2FC>0$',significance_feature+'>='+str(thr_significance),significance_feature+'<'+str(thr_significance)+', $log_2FC<0$']\n",
    "    palette = ['skyblue','grey','green']\n",
    "    \n",
    "    sns.set(font_scale=1)\n",
    "    sns.set_style(\"white\")\n",
    "    fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3),)\n",
    "    \n",
    "    ax = sns.scatterplot(data = data,x=x_feature,y=y_feature,hue=hue,s=2,hue_order = hue_order,palette = palette)\n",
    "    ax = sns.scatterplot(data = data_to_show,x=x_feature,y=y_feature,hue=hue,s=20,edgecolor='black',linewidth=1,hue_order = hue_order,palette = palette,\n",
    "                     alpha=1,legend=None)\n",
    "    for index, row in data_to_show.iterrows():\n",
    "        if genes_of_interest[row['gene_name']]=='JUNB':\n",
    "            ax.text(row[x_feature]*1.05,row[y_feature],genes_of_interest[row['gene_name']],ha='left',va='top',size=10)\n",
    "        else:\n",
    "            ax.text(row[x_feature]*0.95,row[y_feature],genes_of_interest[row['gene_name']],ha='right',va='center',size=10)\n",
    "        \n",
    "    ax.set(xlabel = 'average, $log_2$',title=organism+', '+batch+'\\n'+comparison+', RNA-seq')\n",
    "    ax.set_ylabel(ylabel=r'$log_2FC$',rotation=0,ha='right',va='center',rotation_mode='anchor')\n",
    "    ax.hlines(y=0,xmin=ax.get_xlim()[0],xmax=ax.get_xlim()[1],color='grey',linestyles='--',linewidth=0.7)\n",
    "    \n",
    "    legend_labels = [elem+'\\n'+str(len(data.loc[data[hue]==elem]))+' genes' for elem in hue_order]\n",
    "    h, l = ax.get_legend_handles_labels()\n",
    "    \n",
    "    ax.legend(bbox_to_anchor=(1.001, 0.65),loc=2,borderaxespad=0.0,title='',markerscale=3,handles = h,labels = legend_labels)\n",
    "    ax.tick_params(bottom=True,left=True)\n",
    "    \n",
    "    DE_dict[DE_analysis] = DE_table\n",
    "    \n",
    "    out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/'+'by_'+significance_feature+'/', shell=True)\n",
    "    fig.savefig(subdirs['figures_dir']+'RNAseq/'+'by_'+significance_feature+'/'+'_'.join([organism,batch,comparison])+'_MA_plot.png',bbox_inches='tight',dpi=600)\n",
    "    fig.savefig(subdirs['figures_dir']+'RNAseq/'+'by_'+significance_feature+'/'+'_'.join([organism,batch,comparison])+'_MA_plot.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b424761-4b89-4598-bf4a-8eb1c312dcc0",
   "metadata": {},
   "source": [
    "## Compare Deseq2 with PROseq and bCLIP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4e5113f4-cdc6-4dc1-981e-08b0ae73baf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "DE_analysis = 'mouse;public;si_Ints11_vs_si_CTRL'\n",
    "significance_feature = 'FDR'\n",
    "bCLIP_replicates_to_show = ['Ints11C_replicate6','Ints10N_replicate1']\n",
    "DE_table = DE_dict[DE_analysis]\n",
    "\n",
    "data_PROseq = pd.read_csv(subdirs['tables_dir']+'PROseq_quantification/'+'PROseq.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "data_PROseq['gene_name'] = data_PROseq['TSS'].str.split(';',expand=True)[0]\n",
    "\n",
    "data_bCLIP = pd.read_csv(subdirs['tables_dir']+'bCLIP_quantification/'+'bCLIP.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "intersection = pd.merge(data_PROseq,data_bCLIP[['TSS']+list(pd.Series(bCLIP_replicates_to_show)+';sign')],how='inner',on='TSS')\n",
    "intersection = pd.merge(intersection,DE_table[['gene_name','log2_mean','log2FoldChange','RNAseq_cat']],how='left',on='gene_name')\n",
    "bCLIP_samples = []\n",
    "for sample in bCLIP_replicates_to_show:\n",
    "    new_sample = sample.split('_')[0]+'+'\n",
    "    bCLIP_samples.append(new_sample)\n",
    "    intersection = intersection.rename(columns = {sample+';sign':new_sample})\n",
    "intersection = intersection.dropna().reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c2856ef5-1357-4f32-85df-3eb878693062",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import textwrap\n",
    "wrapper = textwrap.TextWrapper(width=10)\n",
    "\n",
    "x_feature = 'PROseq_cat'\n",
    "order = ['pval<'+str(thr_significance)+', $log_2OR>0$','pval>='+str(thr_significance),'pval<'+str(thr_significance)+', $log_2OR<0$']\n",
    "palette = ['orange','grey','purple']\n",
    "order_labels = ['pval<'+str(thr_significance)+',\\n$log_2OR>0$','pval>='+str(thr_significance),'pval<'+str(thr_significance)+',\\n$log_2OR<0$']\n",
    "\n",
    "y_feature = 'Ints11C+'\n",
    "\n",
    "hue = 'RNAseq_cat'\n",
    "hue_order = [significance_feature+'<'+str(thr_significance)+', $log_2FC>0$',significance_feature+'>='+str(thr_significance),\n",
    "             significance_feature+'<'+str(thr_significance)+', $log_2FC<0$']\n",
    "hue_palette = ['skyblue','grey','green']\n",
    "\n",
    "def func1(x):\n",
    "    return 100*np.mean(x)+1\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(3,1,sharey=True,sharex=True, figsize=(3,3))\n",
    "\n",
    "j=0\n",
    "for cat in order:\n",
    "    ax = sns.barplot(ax=axes[j],data = intersection.loc[intersection[x_feature]==cat], y=hue, x=y_feature, estimator=func1,\n",
    "                order=hue_order,palette = hue_palette,hue=hue,hue_order=hue_order,\n",
    "                orient='h',\n",
    "                 capsize=0.1,errwidth=1)\n",
    "    ax.legend([])\n",
    "    # if j==1:\n",
    "    #     ax.legend(bbox_to_anchor=(1.001, 1.2),loc=2,borderaxespad=0.0,title='RNA-seq',markerscale=3)\n",
    "    ax.yaxis.label.set_color(palette[j])\n",
    "    ax.set(yticklabels=[],xlabel='',xlim=(0,70))\n",
    "    ax.set_ylabel(ylabel=order_labels[j],rotation=0,ha='right',va='center',rotation_mode='anchor')\n",
    "    \n",
    "    j=j+1\n",
    "ax.set(xlabel='% of '+y_feature+' targets')\n",
    "ax.tick_params(bottom=True)\n",
    "fig.suptitle('PRO-seq', x=-0.13,y=0.95,size=12,ha='left',va='top')\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'association_between_RNA_seq_PRO_seq_and_bCLIP.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'association_between_RNA_seq_PRO_seq_and_bCLIP.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6ed785e2-7e73-42df-88b5-4dad897a3aba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib_venn import venn3,venn3_circles\n",
    "from matplotlib_venn import venn2,venn2_circles\n",
    "\n",
    "intersection['RNA-seq - down'] = (intersection['RNAseq_cat']==significance_feature+'<'+str(thr_significance)+', $log_2FC<0$').astype('int')\n",
    "intersection['RNA-seq - up'] = (intersection['RNAseq_cat']==significance_feature+'<'+str(thr_significance)+', $log_2FC>0$').astype('int')\n",
    "intersection['PRO-seq - up'] = (intersection['PROseq_cat']=='pval<'+str(thr_significance)+', $log_2OR>0$').astype('int')\n",
    "intersection['PRO-seq - down'] = (intersection['PROseq_cat']=='pval<'+str(thr_significance)+', $log_2OR<0$').astype('int')\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(2, 2, sharey=False, sharex=False, figsize=(12,12))\n",
    "\n",
    "# first\n",
    "labels_of_interest = ['Ints11C+','RNA-seq - up','PRO-seq - up']\n",
    "labels_to_show = ['bCLIP Ints11C +','RNA-seq - up','PRO-seq - up']\n",
    "palette = ['pink','skyblue','orange']\n",
    "ax = sns.scatterplot(ax=axes[0][0],data = None)\n",
    "data = intersection.copy()\n",
    "\n",
    "TSS_lists = []\n",
    "for label in labels_of_interest:\n",
    "    TSS_list = set(list(data.loc[data[label]==1]['TSS'].astype('str')))\n",
    "    TSS_lists.append(TSS_list)\n",
    "    \n",
    "v = venn3(TSS_lists,set_labels=labels_to_show,set_colors=palette,ax=ax,alpha=1)\n",
    "c = venn3_circles(TSS_lists,color='black',linewidth=1,ax=ax)\n",
    "\n",
    "# second\n",
    "labels_of_interest = ['Ints11C+','RNA-seq - down','PRO-seq - up']\n",
    "labels_to_show = ['bCLIP Ints11C +','RNA-seq - down','PRO-seq - up']\n",
    "palette = ['pink','green','orange']\n",
    "ax = sns.scatterplot(ax=axes[0][1],data = None)\n",
    "data = intersection.copy()\n",
    "\n",
    "TSS_lists = []\n",
    "for label in labels_of_interest:\n",
    "    TSS_list = set(list(data.loc[data[label]==1]['TSS'].astype('str')))\n",
    "    TSS_lists.append(TSS_list)\n",
    "    \n",
    "v = venn3(TSS_lists,set_labels=labels_to_show,set_colors=palette,ax=ax,alpha=1)\n",
    "c = venn3_circles(TSS_lists,color='black',linewidth=1,ax=ax)\n",
    "\n",
    "# third\n",
    "labels_of_interest = ['Ints11C+','RNA-seq - up','PRO-seq - down']\n",
    "labels_to_show = ['bCLIP Ints11C +','RNA-seq - up','PRO-seq - down']\n",
    "palette = ['pink','skyblue','purple']\n",
    "ax = sns.scatterplot(ax=axes[1][0],data = None)\n",
    "data = intersection.copy()\n",
    "\n",
    "TSS_lists = []\n",
    "for label in labels_of_interest:\n",
    "    TSS_list = set(list(data.loc[data[label]==1]['TSS'].astype('str')))\n",
    "    TSS_lists.append(TSS_list)\n",
    "    \n",
    "v = venn3(TSS_lists,set_labels=labels_to_show,set_colors=palette,ax=ax,alpha=1)\n",
    "c = venn3_circles(TSS_lists,color='black',linewidth=1,ax=ax)\n",
    "\n",
    "# forth\n",
    "labels_of_interest = ['Ints11C+','RNA-seq - down','PRO-seq - down']\n",
    "labels_to_show = ['bCLIP Ints11C +','RNA-seq - down','PRO-seq - down']\n",
    "palette = ['pink','green','purple']\n",
    "ax = sns.scatterplot(ax=axes[1][1],data = None)\n",
    "data = intersection.copy()\n",
    "\n",
    "TSS_lists = []\n",
    "for label in labels_of_interest:\n",
    "    TSS_list = set(list(data.loc[data[label]==1]['TSS'].astype('str')))\n",
    "    TSS_lists.append(TSS_list)\n",
    "    \n",
    "v = venn3(TSS_lists,set_labels=labels_to_show,set_colors=palette,ax=ax,alpha=1)\n",
    "c = venn3_circles(TSS_lists,color='black',linewidth=1,ax=ax)\n",
    "\n",
    "# fig.tight_layout(pad=5.5)\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/Vienn_Diagrams.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/Vienn_Diagrams.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ae049ae3-ca27-4bc5-8901-784b800e4e1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make heatmap with Jaccard similarity\n",
    "RNAseq_cat_dict = {'FDR<0.05, $log_2FC>0$':1,'FDR>=0.05':0,'FDR<0.05, $log_2FC<0$':-1}\n",
    "intersection['RNAseq_cat_int'] = intersection['RNAseq_cat'].map(RNAseq_cat_dict)\n",
    "PROseq_cat_dict = {'pval<0.05, $log_2OR>0$':1, 'pval>=0.05':0, 'pval<0.05, $log_2OR<0$':-1}\n",
    "intersection['PROseq_cat_int'] = intersection['PROseq_cat'].map(PROseq_cat_dict)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0213d6c4-6392-41a7-b286-f6c43af62c49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "list_of_features = ['Ints11C+','PROseq_cat_int','RNAseq_cat_int']\n",
    "feature_labels = ['Ints11 bCLIP','PRO-seq','RNA-seq']\n",
    "from sklearn.metrics.pairwise import pairwise_distances\n",
    "A = 1 - pairwise_distances(intersection[list_of_features].T.to_numpy(), metric='cosine')\n",
    "A = pd.DataFrame(A,columns = feature_labels)\n",
    "A.index = feature_labels\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3))\n",
    "\n",
    "ax = sns.heatmap(A,cbar_kws={'label': 'cosine similarity'},vmin=-0.2,vmax=0.2,center=0,cmap=sns.color_palette('vlag',as_cmap=True),annot=True)\n",
    "ax.set(xlabel=\"\", ylabel=\"\")\n",
    "\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/cosine_similarity.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/cosine_similarity.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7dd40da6-ef91-4d09-9fae-760c29984168",
   "metadata": {},
   "outputs": [],
   "source": [
    "targets_plus_plus_plus = intersection.loc[(intersection['Ints11C+']==1)&(intersection['PROseq_cat_int']==1)&(intersection['RNAseq_cat_int']==1)][['gene_name']].drop_duplicates()\n",
    "targets_plus_plus_minus = intersection.loc[(intersection['Ints11C+']==1)&(intersection['PROseq_cat_int']==1)&(intersection['RNAseq_cat_int']==-1)][['gene_name']].drop_duplicates()\n",
    "targets_plus_minus_plus = intersection.loc[(intersection['Ints11C+']==1)&(intersection['PROseq_cat_int']==-1)&(intersection['RNAseq_cat_int']==1)][['gene_name']].drop_duplicates()\n",
    "targets_plus_minus_minus = intersection.loc[(intersection['Ints11C+']==1)&(intersection['PROseq_cat_int']==-1)&(intersection['RNAseq_cat_int']==-1)][['gene_name']].drop_duplicates()\n",
    "background = intersection[['gene_name']].drop_duplicates()\n",
    "\n",
    "targets_plus_plus_plus.to_csv(subdirs['tables_dir']+'GO_enrichment/targets_plus_plus_plus.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_plus_plus_minus.to_csv(subdirs['tables_dir']+'GO_enrichment/targets_plus_plus_minus.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_plus_minus_plus.to_csv(subdirs['tables_dir']+'GO_enrichment/targets_plus_minus_plus.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_plus_minus_minus.to_csv(subdirs['tables_dir']+'GO_enrichment/targets_plus_minus_minus.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "background.to_csv(subdirs['tables_dir']+'GO_enrichment/bclip_background.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "938fb06d-df68-4e96-8288-0589cc789181",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Ints1',\n",
       " 'Ints2',\n",
       " 'Ints3',\n",
       " 'Ints4',\n",
       " 'Ints5',\n",
       " 'Ints6',\n",
       " 'Ints7',\n",
       " 'Ints8',\n",
       " 'Ints9',\n",
       " 'Ints10',\n",
       " 'Ints11',\n",
       " 'Ints12',\n",
       " 'Ints13']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4355255b-b583-450f-b82f-bfe603b1c5d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TSS</th>\n",
       "      <th>gene_name</th>\n",
       "      <th>Ints11C+</th>\n",
       "      <th>Ints10N+</th>\n",
       "      <th>PROseq_cat_int</th>\n",
       "      <th>RNAseq_cat_int</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Junb;85705347</td>\n",
       "      <td>Junb</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ddx11;66430515</td>\n",
       "      <td>Ddx11</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ints1;139761429</td>\n",
       "      <td>Ints1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ints2;86148401</td>\n",
       "      <td>Ints2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ints3;90340929</td>\n",
       "      <td>Ints3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ints4;97130163</td>\n",
       "      <td>Ints4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ints5;8870369</td>\n",
       "      <td>Ints5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Ints6;62998618</td>\n",
       "      <td>Ints6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Ints7;191307748</td>\n",
       "      <td>Ints7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Ints8;11254258</td>\n",
       "      <td>Ints8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Ints9;65187494</td>\n",
       "      <td>Ints9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ints10;69246581</td>\n",
       "      <td>Ints10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ints11;155954003</td>\n",
       "      <td>Ints11</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Ints12;132797601</td>\n",
       "      <td>Ints12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Ints13;146479333</td>\n",
       "      <td>Ints13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Ints6l;55500217</td>\n",
       "      <td>Ints6l</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 TSS gene_name  Ints11C+  Ints10N+  PROseq_cat_int  \\\n",
       "0      Junb;85705347      Junb         1         1               1   \n",
       "1     Ddx11;66430515     Ddx11         1         1               1   \n",
       "2    Ints1;139761429     Ints1         0         0               1   \n",
       "3     Ints2;86148401     Ints2         1         0               0   \n",
       "4     Ints3;90340929     Ints3         1         0               0   \n",
       "5     Ints4;97130163     Ints4         1         0               0   \n",
       "6      Ints5;8870369     Ints5         0         0               0   \n",
       "7     Ints6;62998618     Ints6         1         1               0   \n",
       "8    Ints7;191307748     Ints7         0         0               0   \n",
       "9     Ints8;11254258     Ints8         1         1               1   \n",
       "10    Ints9;65187494     Ints9         0         0               0   \n",
       "11   Ints10;69246581    Ints10         1         0               1   \n",
       "12  Ints11;155954003    Ints11         1         1               0   \n",
       "13  Ints12;132797601    Ints12         0         0               0   \n",
       "14  Ints13;146479333    Ints13         1         0               1   \n",
       "15   Ints6l;55500217    Ints6l         1         0               1   \n",
       "\n",
       "    RNAseq_cat_int  \n",
       "0               -1  \n",
       "1               -1  \n",
       "2                0  \n",
       "3                0  \n",
       "4                1  \n",
       "5               -1  \n",
       "6                0  \n",
       "7                0  \n",
       "8                0  \n",
       "9                0  \n",
       "10               0  \n",
       "11              -1  \n",
       "12              -1  \n",
       "13               0  \n",
       "14               1  \n",
       "15               0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TSS_summary = intersection[['TSS','gene_name','Ints11C+','Ints10N+','PROseq_cat_int','RNAseq_cat_int']]\n",
    "TSS_summary.to_csv(subdirs['tables_dir']+'TSS_summary.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)\n",
    "\n",
    "genes_of_interest = ['Junb','Ddx11']+list('Ints'+pd.Series(range(1,14)).astype('str'))+list('Ints'+pd.Series(range(1,14)).astype('str')+'l')\n",
    "TSS_summary_filtered = TSS_summary.loc[TSS_summary['gene_name'].isin(genes_of_interest)].reset_index(drop=True)\n",
    "sort_dict = {}\n",
    "i=0\n",
    "for elem in genes_of_interest:\n",
    "    sort_dict[elem]=i\n",
    "    i=i+1\n",
    "TSS_summary_filtered['order'] = TSS_summary_filtered['gene_name'].map(sort_dict)\n",
    "TSS_summary_filtered = TSS_summary_filtered.sort_values('order').reset_index(drop=True)\n",
    "TSS_summary_filtered = TSS_summary_filtered.drop('order',1)\n",
    "TSS_summary_filtered.to_csv(subdirs['tables_dir']+'TSS_summary_filtered.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)\n",
    "TSS_summary_filtered"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36d764d0-218a-4796-8897-02542cf17465",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Compare Deseq2 Ints6, Ints6L, and Ints13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "39cce222-2009-4358-9dbe-2bd74bc0d12b",
   "metadata": {},
   "outputs": [],
   "source": [
    "significance_feature = 'pvalue'\n",
    "thr_significance = 0.05\n",
    "DE_analysis_1 = 'human;in-house;si_INTS6_vs_si_CTRL'\n",
    "DE_analysis_2 = 'human;in-house;si_INTS6L_vs_si_CTRL'\n",
    "DE_table_1 = DE_dict[DE_analysis_1]\n",
    "DE_table_2 = DE_dict[DE_analysis_2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "43963d65-2fc2-4e51-b7ba-5d3554423426",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make MA-plot for Ints13\n",
    "DE_table_Ints13 = pd.read_csv(subdirs['tables_dir']+'Deseq2/results_DESeq_ints13_Depletion_vs_negctrl.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "used_genes = list(DE_table_1['gene_id'].str.split('.',expand=True)[0].unique())\n",
    "DE_table_Ints13 = DE_table_Ints13.loc[DE_table_Ints13['ID'].isin(used_genes)].drop_duplicates('ID').reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "94897a08-f6d4-4c7c-b958-c5ae0e9b460b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "targeted_gene_name = 'INTS13'\n",
    "# genes_of_interest = {targeted_gene_name:targeted_gene_name}\n",
    "genes_of_interest = {targeted_gene_name:targeted_gene_name,'JUNB':'JUNB','Junb':'Junb'}\n",
    "\n",
    "DE_table_Ints13['sign'] = (DE_table_Ints13[significance_feature]<thr_significance).astype('int')\n",
    "map_dict = {-1:significance_feature+'<'+str(thr_significance)+', $log_2FC<0$',1:significance_feature+'<'+str(thr_significance)+', $log_2FC>0$',0:significance_feature+'>='+str(thr_significance)}\n",
    "DE_table_Ints13['RNAseq_cat'] = (DE_table_Ints13['sign']*((DE_table_Ints13['log2FoldChange']>0).astype('int')*2-1)).map(map_dict)\n",
    "DE_table_Ints13['log2_mean'] = np.log2(DE_table_Ints13['baseMean'])\n",
    "\n",
    "data = DE_table_Ints13.copy()\n",
    "data_to_show = data.loc[data['gene_name'].isin(genes_of_interest)].reset_index(drop=True)\n",
    "\n",
    "x_feature,y_feature,hue = 'log2_mean','log2FoldChange','RNAseq_cat'\n",
    "hue_order = [significance_feature+'<'+str(thr_significance)+', $log_2FC>0$',significance_feature+'>='+str(thr_significance),significance_feature+'<'+str(thr_significance)+', $log_2FC<0$']\n",
    "palette = ['skyblue','grey','green']\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3),)\n",
    "\n",
    "ax = sns.scatterplot(data = data,x=x_feature,y=y_feature,hue=hue,s=2,hue_order = hue_order,palette = palette)\n",
    "ax = sns.scatterplot(data = data_to_show,x=x_feature,y=y_feature,hue=hue,s=20,edgecolor='black',linewidth=1,hue_order = hue_order,palette = palette,\n",
    "                 alpha=1,legend=None)\n",
    "for index, row in data_to_show.iterrows():\n",
    "    if genes_of_interest[row['gene_name']]=='JUNB':\n",
    "        ax.text(row[x_feature]*1.05,row[y_feature],genes_of_interest[row['gene_name']],ha='left',va='top',size=10)\n",
    "    else:\n",
    "        ax.text(row[x_feature]*0.95,row[y_feature],genes_of_interest[row['gene_name']],ha='right',va='center',size=10)\n",
    "    \n",
    "ax.set(xlabel = 'average, $log_2$',title='human, in-house\\n'+'si_INTS13_vs_si_CTRL, RNA-seq')\n",
    "ax.set_ylabel(ylabel=r'$log_2FC$',rotation=0,ha='right',va='center',rotation_mode='anchor')\n",
    "ax.hlines(y=0,xmin=ax.get_xlim()[0],xmax=ax.get_xlim()[1],color='grey',linestyles='--',linewidth=0.7)\n",
    "\n",
    "legend_labels = [elem+'\\n'+str(len(data.loc[data[hue]==elem]))+' genes' for elem in hue_order]\n",
    "h, l = ax.get_legend_handles_labels()\n",
    "\n",
    "ax.legend(bbox_to_anchor=(1.001, 0.65),loc=2,borderaxespad=0.0,title='',markerscale=3,handles = h,labels = legend_labels)\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/'+'by_'+significance_feature+'/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'by_'+significance_feature+'/'+'human_in-house_'+'si_INTS13_vs_si_CTRL'+'_MA_plot.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'by_'+significance_feature+'/'+'human_in-house_'+'si_INTS13_vs_si_CTRL'+'_MA_plot.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c77daad9-748e-4e53-bb1d-b287beee2b67",
   "metadata": {},
   "outputs": [],
   "source": [
    "DE_table_3 = DE_table_Ints13.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "52b41bd2-9300-4258-bc2b-7beafa0065f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(19881, 19881, 19881)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(DE_table_1),len(DE_table_2),len(DE_table_3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "eb5ea2c8-2fbd-476b-b3e9-92af8e1a12e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# first, Ints6 vs 6L\n",
    "RNAseq_cat_dict = {significance_feature+'<0.05, $log_2FC>0$':1,significance_feature+'>=0.05':0,significance_feature+'<0.05, $log_2FC<0$':-1}\n",
    "\n",
    "features_of_interest = ['log2FoldChange','pvalue','minus_log_pval','RNAseq_cat']\n",
    "experiment_labels = ['si INTS6','si INTS6L','si INTS13']\n",
    "\n",
    "i=0\n",
    "for DE_table in [DE_table_1,DE_table_2,DE_table_3]:\n",
    "    data = DE_table.copy()\n",
    "    if 'ID' not in list(data.columns):\n",
    "        data['ID'] = data['gene_id'].str.split('.',expand=True)[0]\n",
    "    data = data.sort_values('ID').drop_duplicates('ID').reset_index(drop=True)\n",
    "    data['minus_log_pval'] = (-1)*np.log10(data['pvalue']+10**(-20))*((data['log2FoldChange']>0).astype('int')*2-1)\n",
    "    data['RNAseq_cat'] = data['RNAseq_cat'].map(RNAseq_cat_dict)\n",
    "    rename_dict = {}\n",
    "    for feature in features_of_interest:\n",
    "        rename_dict[feature] = feature+'_'+str(i+1)\n",
    "    if i==0:\n",
    "        intersection = data[['ID','gene_name']+features_of_interest].rename(columns = rename_dict)\n",
    "    else:\n",
    "        intersection = pd.merge(intersection,data[['ID']+features_of_interest].rename(columns = rename_dict),how='inner',on=['ID'])\n",
    "    i=i+1\n",
    "intersection = intersection.dropna().reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "id": "0c60aa95-4120-48ca-af31-3a13a0b8ff65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 100x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(1,3))\n",
    "\n",
    "feature = 'log2FoldChange'\n",
    "\n",
    "genes_of_interest = {'JUNB':'JUNB'}\n",
    "\n",
    "data = intersection.loc[abs(intersection['RNAseq_cat_1'])+abs(intersection['RNAseq_cat_2'])+abs(intersection['RNAseq_cat_3'])>=1].reset_index(drop=True)\n",
    "data['av_cat'] =((data['log2FoldChange_1']>0).astype('int')*2-1)+((data['log2FoldChange_2']>0).astype('int')*2-1)+((data['log2FoldChange_3']>0).astype('int')*2-1)\n",
    "data['av_effect'] = data[[feature+'_1',feature+'_2',feature+'_3']].median(1)\n",
    "data = data.sort_values(['av_cat','av_effect'],ascending=[False,False]).reset_index(drop=True)\n",
    "\n",
    "data['all_up'] = ((data['log2FoldChange_1']>0).astype('int')+(data['log2FoldChange_2']>0).astype('int')+(data['log2FoldChange_3']>0).astype('int')==3).astype('int')\n",
    "data['all_down'] = ((data['log2FoldChange_1']<0).astype('int')+(data['log2FoldChange_2']<0).astype('int')+(data['log2FoldChange_3']<0).astype('int')==3).astype('int')\n",
    "\n",
    "data_to_show = data.loc[data['gene_name'].isin(genes_of_interest)]\n",
    "\n",
    "ax = sns.heatmap(data[[feature+'_1',feature+'_2',feature+'_3']],cbar_kws={'label': '$log_2FC$','aspect':20},vmin=-2,vmax=2,center=0,cmap=sns.color_palette('vlag',as_cmap=True))\n",
    "ax.set(xticklabels=experiment_labels,ylabel='',yticks=[],title='at least\\none experiment\\n#='+str(len(data)))\n",
    "\n",
    "# for index, row in data_to_show.iterrows():\n",
    "#     ax.text(0,index,'< '+genes_of_interest[row['gene_name']],ha='left',va='center',size=10)\n",
    "\n",
    "y_pos = np.max(list(data.loc[data['all_up']==1].index))\n",
    "ax.text(0,y_pos,'_ _ _ _ _ _ _ ',ha='right',va='bottom',size=10)\n",
    "ax.text(0,y_pos*0.9,'$Log_2FC>0$\\n'+str(len(data.loc[data['all_up']==1]))+' genes',ha='right',va='bottom',size=10)\n",
    "\n",
    "y_pos = np.min(list(data.loc[data['all_down']==1].index))\n",
    "ax.text(0,y_pos,'_ _ _ _ _ _ _ ',ha='right',va='top',size=10)\n",
    "ax.text(0,y_pos*1.1,'$Log_2FC<0$\\n'+str(len(data.loc[data['all_down']==1]))+' genes',ha='right',va='top',size=10)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_6L_vs_11_heatmap.1.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_6L_vs_11_heatmap.1.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 510,
   "id": "35a2e0fd-2aac-4648-a1cf-cc23fd450b75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 100x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(1,3))\n",
    "\n",
    "feature = 'log2FoldChange'\n",
    "\n",
    "genes_of_interest = {'JUNB':'JUNB'}\n",
    "\n",
    "data = intersection.loc[abs(intersection['RNAseq_cat_1'])+abs(intersection['RNAseq_cat_2'])+abs(intersection['RNAseq_cat_3'])>=2].reset_index(drop=True)\n",
    "data['av_cat'] =((data['log2FoldChange_1']>0).astype('int')*2-1)+((data['log2FoldChange_2']>0).astype('int')*2-1)+((data['log2FoldChange_3']>0).astype('int')*2-1)\n",
    "data['av_effect'] = data[[feature+'_1',feature+'_2',feature+'_3']].median(1)\n",
    "data = data.sort_values(['av_cat','av_effect'],ascending=[False,False]).reset_index(drop=True)\n",
    "\n",
    "data['all_up'] = ((data['log2FoldChange_1']>0).astype('int')+(data['log2FoldChange_2']>0).astype('int')+(data['log2FoldChange_3']>0).astype('int')==3).astype('int')\n",
    "data['all_down'] = ((data['log2FoldChange_1']<0).astype('int')+(data['log2FoldChange_2']<0).astype('int')+(data['log2FoldChange_3']<0).astype('int')==3).astype('int')\n",
    "\n",
    "data_to_show = data.loc[data['gene_name'].isin(genes_of_interest)]\n",
    "\n",
    "ax = sns.heatmap(data[[feature+'_1',feature+'_2',feature+'_3']],cbar_kws={'label': '$log_2FC$','aspect':20},vmin=-2,vmax=2,center=0,cmap=sns.color_palette('vlag',as_cmap=True))\n",
    "ax.set(xticklabels=experiment_labels,ylabel='',yticks=[],title='at least\\ntwo experiments\\n#='+str(len(data)))\n",
    "\n",
    "# for index, row in data_to_show.iterrows():\n",
    "#     ax.text(0,index,'< '+genes_of_interest[row['gene_name']],ha='left',va='center',size=10)\n",
    "\n",
    "y_pos = np.max(list(data.loc[data['all_up']==1].index))\n",
    "ax.text(0,y_pos,'_ _ _ _ _ _ _ ',ha='right',va='bottom',size=10)\n",
    "ax.text(0,y_pos*0.9,'$Log_2FC>0$\\n'+str(len(data.loc[data['all_up']==1]))+' genes',ha='right',va='bottom',size=10)\n",
    "\n",
    "y_pos = np.min(list(data.loc[data['all_down']==1].index))\n",
    "ax.text(0,y_pos,'_ _ _ _ _ _ _ ',ha='right',va='top',size=10)\n",
    "ax.text(0,y_pos*1.1,'$Log_2FC<0$\\n'+str(len(data.loc[data['all_down']==1]))+' genes',ha='right',va='top',size=10)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_6L_vs_11_heatmap.2.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_6L_vs_11_heatmap.2.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "id": "207992cc-240b-4ba8-aad3-6b400393180d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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e0MjICPr6+rzXTVdXl32puLi4wMnJCT4+PggKCsLYsWNlysfGxiIyMhJjxozhbP0wUTNIyAIzduxYqXxc0dHR2L17N3s8btw4AECXLl3YlDdCNa3L4+DgAHV19Upzj5W1EoYNG8bZM4maQUIWmJUrVyI3Nxd//vknduzYgcDAQKirq2P79u3IycnBggULAEin+hGqaV2esLAwlJSUoGXLljLXCgsLcebMGTg6OrKJHgjFQUIWmLLskT/99BNcXV3ZND8xMTHw8/OrMKDC2NiYzbVVHfLy8nD16lUApfPTQGlzPiMjAw0aNGAX6//+++84duwYevfujWbNmqGoqAiRkZEIDAxEy5YtK/S4ly5dwps3bzB37txq14vgHhKyAigpKcGVK1cwa9YsAKXN65cvX8Ld3Z3T56SlpWHmzJlS57Zu3QqgNE1uWRhoixYtoKmpiZ07d7LJ+5o1a4ahQ4fCz8+vwv75iRMnoKuriwEDBnBaZ6Jm0DJGglABKLKLIFQAaloT9YKff/4ZZ86cQVRUFDIzM2FpaYkRI0Zg+PDhtQ5lrQtQ05qoF/j4+MDCwgJ9+/aFiYkJbt26hYCAAIwZM4adKVBmSMhEvSA9PV0mze3atWtx5MgR3LlzR+kDWpS/TUEQclBRrmpbW1sUFBTgzZs3wleIY0jIRL0lPDwcRkZGMDExUXRVag0NdhF1lj59+rz3+m+//VZj2xEREQgODsa0adNUIhkCCVkgjnXroegqKASfv/6QOq7W99BQm+PalPL69WvMmDED7du3h6+vLy/PEBoSMiEs6vJv0Vobj1sZ2dnZ8PX1hY6ODnbu3AlNTU3On6EISMgC0bCp7AbktUE8wodTewCQGR/Puc3yqKkpblimoKAAU6ZMQWpqKoKCgmoUv15XISELhEUPV07tSarY87cmpEfHcm6zPGrV8MhcUlxcjJkzZyI2NhaHDh1Suv2Pq4KETAiKooS8atUq/P7775g3bx7y8/Nx79499lqbNm042VtbkZCQBSLr8RNO7Wn9m8+LS+wmjOfcZnnUFDRC/McfpYNuGzZskLnG5d7aioKETAhKWf5uoeFi5466DAlZIJp04/aNr9ukCaf2AODBTz9xbrN574+kjtVUYIFCXYSETAiLgvrIqg4JWSC4blLmp6Vzag8ALPv149xmeRTVtFZ1SMgCoa7FbZSSiYMDp/YAICXsFuc2y0NNa34gIROCQh6ZH0jIAlGUk82pvdwXzzm1BwAaug2rLlRbqI/MCyRkQlAUGaKpypCQBULb0IhTe+kRkZzaA4DmH/G/f5OiIrtUHRKyUHD8AzbkYXeHpF8vcm7TxEE64b6iIrtUHRIyISjkkfmBhCwQWgYGnNorzs3l1B4AFOXkcG6zPNRH5gcSMiEs5JF5gYQsEFx7UL0Wsjsk1hZJYSHnNstD88j8QEIWiAaNuV3kkJOUxKk9AMj/dwM3PqHILn4gIRPCQh6ZF0jIAvH25UtO7anzkDTOsG1bzm2WhzwyP5CQCUGhPjI/kJAFouBNBqf2DNtw7z0Ls7I4t1keCgjhBxKyQHC9IIGPOV99S0vObZaHAkL4gYRMCAoFhPADCVkgDK2sOLWXn57GqT0AeBV+h3ObJu2dpE+QR+YFEjIhKDTYxQ8kZIHI4zjYguvYbQBoaGHBuc3y0PQTP5CQBYLr0doiHhZNQIj+K3lkXiAhE4JCHpkfSMgCwUckFteUFBbw/xDyyLxAQiYERZ0CQniBhCwQGjo6nNor5mFb1axHjzi3KQNNP/ECCVkgSoqKOLWnxcM2oCVFxZzbLA8FhPADCZkQFArR5AcSspJSnJfHuU11TQF+DuSReYGETAgKeWR+ICELBcfTLlwPngGAsa0d5zbLQ31kfiAhE8JCHpkXSMgCoa7B7VfNR4AJ5bVWXkjIQsFx05qPeWQhBrsoQwg/kJAJQaHBLn4gIQsE16GJDMNwag8QJq81xVrzAwmZEBRa/cQPtRby8OHD0bZtW3zzzTdc1KdafP7557hzRzo9jbq6Om7fvg29f0MYIyMjsXfvXty+fRuZmZlo0qQJXFxc4Ofnh9atW3NWl8OHD2Pv3r14/fo12rZti8WLF6Nz587sda49aPHbt5zaAwCT9o6c2ywPZQjhh1oJuaSkBHFxcfDy8uKqPnLDMAxiYmKwYMECDB48mD2vrq7Oivj48eNYvnw5Pv30U2zbtg1mZmZITEzEwYMHceLECcybN0/KZkpKCkxMTKBRzRHm8+fPY+3atVi+fDmcnZ1x9OhR+Pr64ty5c7D4N+sG101rDV1dTu0B/AygyUAemRdq9a0+evQIb9++hb29fYXXHzx4AF9fXzg7O6N79+5Yt24dCsttFPbw4UN8/vnncHR0hJeXF8LDw2FjY4PY2Nj3PvvJkyfIzc1F586dYWZmxv6ZmJgAAO7cuYNly5Zh6dKlWLVqFTp06IBmzZrB1dUVO3bsgK+vr4zN48ePw83NDevWrUNcXJzc38O+ffswdOhQDBs2DNbW1liyZAmaNm2KI0eOyG2jvqCmpib3HyE/tfLIUVFR0NDQgI2Njcy16OhojBo1CqNHj8bSpUuRkpKCOXPmQF9fH9OmTQNQKmIfHx+MGTMGq1atQkJCAmbOnAlNTU1YVZF1suzZ7dq1q/D6unXr4OLigpEjR1Z43cjISOacr68vrKyscOrUKXzyyScQi8UYMmQIBg8ejEaNGlVop7CwEFFRUfDz85M63717d9y9e5c9zkvjNuuljrExp/YAfry8DDSPzAu1EnJ0dDSsra2hra0tc23p0qXw8vLC7NmzAQAtW7aEj48Prly5wgp51apVcHNzY8tYW1vj9OnTSEpKgpaWFl68eIH58+cjLS0NIpEIU6dOhaenJ4BSIUskEnTt2pV9plgsRlBQEBISEhAREYEtW7ZU6/Noa2tjwIABGDBgANLS0nDmzBmEhoZiw4YN6NWrF7y9veHu7i7V9M7IyIBEImFbAmWYmpri9evX1Xp+fYCmn/ih1kKuqFmdkJCAqKgobNiwQeq8pqYm27R+9uwZwsLCcPbsWakyWlparJcViURYvHgxbG1tkZaWBm9vb7i5uUFXVxdRUVHw9PTErFmz2HsbNGgAoFTkACpt8suDiYkJxo4di7Fjx+Lq1atYtGgRfvvtN4SGhsLW1lamfPmmIMMwUue49qDaRtx75OzEp5zbbGTnIHVMkV38UGMhlw029e/fX+ZafHw8NDU1ZUaF4+PjIRaLAQCxsbHQ1NRE23I7ACYkJMDb2xsA0LhxYzRu3BhAqbAMDQ2RmZkJXV1dxMTEYNasWWjZUnbD7/x/B210a9FUzMnJwcWLF3Hq1CncuXMHLi4umD9/PqytraXKGRsbQyQSIbXcHGxaWhpMTU3ZY66nXbjeSwoAGpiZcW6zPIqM7Hr69Cn27t2L+/fv4+HDh7CyspJxJMpKjYWcmJiI7Oxs2NnJrphp2LAhJBIJiouLoaWlBQB4/vw5Ll68iO3btwMo9bYSiQQFBQVs0zwsLAyxsbEV9rkjIiLAMAzMzc2RlJSErKysCp8NgH05hIeHo2/fvjLX8/PzoVPB6iGJRII//vgDp0+fxqVLl9C0aVN4eXlh3bp17OhzebS0tGBvb48bN25IPevPP/9Enz59KrynPqPIpvXDhw9x9epVODk5oaSkhJegGkVRYyGXNV9FIhEePHjwn0ENDTg5OcHQ0BDfffcdRo8ejWfPnmH16tXw8PCAm5sbgNJmr4aGBr799luMHTsW8fHxWLNmDQDINF0zMjKwYMECrF69GkDp3LBIJKp0oKtjx47o0aMHVq5cidzcXHTs2BElJSWIiIjA0aNHsWLFCrZl8C7+/v7Yt28fPD09sW/fPjg7O8v1XYwbNw7z58+Hg4MDOnbsiKCgILx48QLDhw+X6/6aIKpgXKK25L54zrlNmS1jFNi07t27Nz766CMAwMKFCxEZGamwunBNjYUcExMDAPDx8ZE636FDBwQFBWHHjh343//+h6CgIJiZmcHHxwcTJkxgyzVu3Bhr1qzB999/j+DgYHTv3h2ffPIJQkJCpEaUCwsLMX36dPj5+bHCio6ORuvWrdk+cUXs3LkT+/fvx969e9nBsxYtWsDd3R1t2rSp8B4vLy9MnDixwsG79zFgwABkZGRgx44dePXqFcRiMQICAtCsWbNq2akPKNIjq6vwHLYaU0faFyUlJRgzZgycnZ0xZ84cAKX98Llz56J169b48ssvFVzD2vHyrz85tSf6t8vCqU0ekhWUH+yK2LFN7nvbT53OdXVYyjxyve8j15bbt28jPT0ddnZ2yMjIwJ49e5CcnIxt2/77jw4PD8f58+dhY2ODS5cuAQC+/fbbCvvQdR2uhaeuxX3TWiJAZFd1PHJVYwy//fZbbaujMihMyKmpqfj++++RkpICU1NTuLq64vjx41LN6s6dO1cZ4UUoFzT9xA8KE7Knpycb3FEfkJQLTa0tfHhkQaiGRyaPKz+0jJEQFFrGyA8kZIHgeiCJj4AQbUNDzm2Wh1L98AMJWSDUNbhNlqfbpAmn9gB+1jiXR5GrmvLy8nD16lUAQHJyMnJycnDhwgUAQJcuXSpdGKMMkJAJYVFg0zotLQ0zZ86UOld2HBgYKLUAR9kgIQuESJvb6Sc+porURAJk0VSgR27evHm11pkrE4IKeevWrVLzxEDpcr8bN24AAIqKirB582Zcu3YNSUlJ0NPTwwcffIC5c+eiCQ9NSUJ4aLCLHwT3yG3btsW+ffvYY9E7gx/5+fmIjo7GlClT0K5dO2RlZWHNmjWYMmUKgoODha4qpxS8ecOpPc2GDTm1B/CT9F4GmkfmBcG/VZFIJJWa590BBn19fezbtw8DBgyAlZUVOnTogKVLlyIqKgrPn1ce0F9cXIzVq1ejc+fO6Nq1KzZs2IAFCxZg6tSpbBmGYbB792706dMHjo6O+Pjjj9mBDgC4desWbGxscPPmTXzyySdwcnLC8OHD8ajc5t+XL1/GJ598gvbt26NPnz7Ytm0biov/21d469at+PDDD+Hg4IAePXqwCz2IUtTU1eT+I+RHcI/89OlT9OjRA1paWnBycsKcOXNgaWlZafmcnByoqanBwMCg0jK7d+/GmTNnsHbtWlhZWSEwMBCXLl2SGrzYvHkzfvnlF6xYsQKtWrXC7du3MW/ePDRq1AhdunRhy23atAkLFy5Eo0aNsHz5cixevBhHjx4FAFy/fh3z5s3D0qVL0blzZyQmJuLrr78GAEyfPh0XLlzA/v37sXHjRrRt2xapqalsZJp2BamFagPXHh7gx8vLQB6ZFwQVsqOjI9avX49WrVohLS0NO3fuxPDhw3H27FkYV5BBo6CgAN999x0GDRrEZsasiEOHDsHPz49dD7xs2TJcu3aNvf727Vvs27cPBw4cQMeOHQEAlpaWCA8PR1BQkJSQZ8+ezR77+fnBz8+PXTPt7+8PPz8/NvGBpaUlZs6ciQ0bNmD69Ol48eIFTE1N8cEHH0BTUxMWFhZwdCxNMZuTnFzLb08aPXNzTu0B/CS9Lw95Wn4QVMhla5HL6NChA/r27YvQ0FCMGzdO6lpRURFmz54NhmGwYsWKSm1mZ2cjNTWVFQxQ2ny3t7dHSUkJgNLMJAUFBRg/frzMM8qvfX53QYbZvxkz0tLSYGFhgaioKERERMDf358tU5YcIS8vDx4eHjhw4AA++ugj9OzZE25ubjI5vuo7FBDCDwr9henq6kIsFuPJkydS54uKijBr1iw8e/YMBw4ceK83LqOinFnl/71r1y6Z0W+tcquS3hVdmc2yF0JJSQm+/PJL9OvXT+b52traMDc3x4ULF3Djxg3cvHkTK1euxN69e3Hw4EFhmq1KAC2a4AeFCrmwsBAJCQno1KkTe65MxE+fPkVgYGCFTe530dfXh6mpKf755x92ZweJRIKYmBg2g4i1tTW0tLTw/PlzqWZ0dbGzs8Pjx48rzBNWho6ODvr06YM+ffpg5MiR8PT0xIMHD2Ba6R31C2pa84OgQl6/fj3c3d1hbm6O9PR07Ny5Ezk5OWyfs7i4GDNmzEB0dDR27doFiUTCppQ1NDSU8Z5ljBo1Crt27UKLFi1gZWWFQ4cOITMzk/Woenp6GD9+PNauXQuGYdCpUyfk5OTg7t270NXVZZ9fFdOmTcPkyZNhbm4ODw8PqKurIy4uDnFxcZg9ezaCg4MhkUjg5OSEBg0a4NSpU9DR0YGFhQXUXr3k4Bv8j6LcXE7tAYCOiQCvG/LIvCCokF++fIk5c+bgzZs3MDY2RocOHXDs2DE2Jc7Lly9x+fJlAJDZhuZ9IXS+vr5ITU3FggULIBKJ4OPjgx49ekjNUc+aNQsmJibYtWsXnj17Bn19fdjZ2WHy5Mly179nz57w9/fH9u3bsWfPHmhoaMDKygrDhg0DABgYGCAgIADr1q1DSUkJxGIx/P39YWxsjKwMbhPUa+rrc2oPABJ/uVB1oWpi7yv9/VJACD/UmVQ/XFJSUsKud34377UiyXoUz6m9EomEU3sAkHzld85tlhfyk/Pyp9ZpNWAQ19VRWVRiODU5ORk3btyAi4sLCgsLcfjwYSQnJ0tt7qZomBJu35daPHhkLUMjzm2WhzwyP6iEkNXV1REcHIz169eDYRiIxWLs27dPJpk8oXhosIsfVELI5ubmbPRVXYXr1U98RHY1rcWIvtzQYBcvqISQlYGCzCxO7Wnp8TAvLYDIuN4nmiiFhEwIC/WReYGELBB8DE5xzdtXKZzb1G/ZSuqYNjDnBxIyISg0as0PJGSB4LpvyDAlnNoDAN3GAmRhIY/MCyRkgVDT4HiQp7jqItXl7esXnNuUaVqTR+YFuYX8/PlzDBw4sNLr586dY/cQnjhxIsLDwyssN2nSJKmwyNOnT2P58uUVlrWwsMC5c+ekzpWtJ66I3bt3swsngNJ1yWfOnKmw7ODBg7Fq1Sr2+M6dO/D19a3U9t27d6WOBw4cWGnWkpUrV+Ljjz+u1FZ9hoTMD3KHaBYXFyP5PYvjmzVrxi4BTElJQX4lWR4NDQ2l9nfKyclBWlrFccgaGhoyW5M+ffq00jo0adJEagPztLQ05OTkVFhWT08PJiYm7HF+fj5SUiof7Cm/4ik5OVkqxc+7mJiYyCy9zEvhdtFESVERp/YAoCi34u+qNhjZSK/3fnnrptz3Nu3qynV1VBaVjLWui5CQS0m5fUvue5u4KG+eaaGhPrJAVMcTyYNe88rznNWUq6ncZ9H8tNwOuBQQwg8kZIEQNdDl1B4fqWu7t2/OuU0ZqI/MC/StEoKipqYm958yk5ubC39/f0RFRQnyPPLIAlHC8f7Iyrr4oL6MWh8+fBj+/v4V5nfjg/rxrRJ1BzV1+f+UmF9//RVDhw6FlZVVpWVu3ryJ0aNHs7nPawN5ZIFQ1+T2q1bnOsAEQEJyOuc2zc1NpI7ry3rk+Ph4qZ1OKsLV1RUbN27EmTNn2ESRNYWELBBcjzLz0YfU1uR/RLm+NK1LSkrQUI4UyAMGDJAJeqoJ9eNbJeoM9WWwy8zMDImJiVWWE4vFePGi9qGx5JEFQqSlzam95JIGnNoDAOOHNzi3CadyfcR64pFdXFwQGhqKTz/99L3l1NXVkZVV+6QT9eNbJeoMamrqcv8pMyNGjEB4eDh27Njx3nIJCQlSO5LWFPLIAvG2Ye3/s96lFVNxLHttyLez59xmefgYpKuLODo6YuLEidiyZQsePnyIWbNmycTrp6enY+/evZXma68OJGRCWJTc01aHuXPnQktLC/7+/rh48SI6deoEW1tbmJmZ4fnz5/j555+Rl5cHPz+/Wj+LFk0IRPLzVE7tGaOAU3sAkJVU9eBMdSm/giknqfLVa+XRs6x8jy1lIjIyEjt37sS1a9dQ9M5iF0tLS3zzzTfo1q1brZ9BQhaI/Nfc5sPiY6cJSQPu84rpG0rbzH2WJPe9DXlYGCIUs2bNwsKFC9G0aVP2XF5eHh4+fIjs7GyYmppKbeFbW6hpTQhKfZlHvnDhAsaPHy8l5MTERKl9vLmEhCwQXG/wnZzNvUe21OB+AA0o5+XrSWRXeSQSCYYMGYITJ07A3p77QUUSMiEoyj6tVBv47MWSkJUUS33up3GKNHWqLlRNylusL7HWQkNCFojHadyOMjc15X5gSreE+/RBMtQjj5yezv0ilMogIROCUp9S/UyZMgV6enpo164dxGIx1NTUkJKSwksfmaafBCL2YeUZSGuCmTH3m7jpSrgf7GrQpKnUceGbDLnv1TIy5ro6gnH16lVER0cjOjoaUVFRbOpkNTU1NGjQALa2trC3t4ednR3s7e3Rtm3bWj2PhCwQJORSijLfyH2vpgAbrwvFmzdvEB0djcjISFbgSUlJYBgGampqiImJqZV9aloLhDrHgzySEu63jHkZJn+qWnlpPdhL+oQC55EfP36M1atXIzw8HA0aNMDAgQPx1VdfSeVC5wsjIyN88MEH+OCDD9hzOTk5iIyMrLWIARKyYDRswPFG54XczyNryrEQvtYoaJ1xVlYWvvjiC1hYWGDLli1IT0/H2rVr8ebNG3z33XcKqZOenh66devGSYgmCZkQGMUI+ejRo8jKykJoaCi7bFAkEuGrr77ClClTYG1tLUg9CgoK8OTJE7Ro0QINGkivKQ8PD0enTp1qZJeErKTw0bRubGfHuU0ZFDSNfO3aNbi6ukqt/e3fvz8WL16Mq1evCiLku3fvYsqUKWAYBgUFBZg6darUyidfX1/8/fffNbJdfyb1iLqBmpr8fxySkJAgI1YtLS20aNECCQkJnD6rMtavX4+FCxfi1q1bOHnyJH755RcsWrQIJf++lGsz7kweWSDe5nOb11qThwX6hdnZnNvUbVp1mcro06fPe6//9ttvctvKysqCgYGBzHkDAwNkZmZWu241IT4+HkOGDAEAWFtb49ChQ5g5cyZmzJiBjRs31so2CVkgioq5bwpzjY4xt1lMKqZuhWiWTf8IgZ6eHlJSUtCkSemG8jo6Oti+fTsWLFiAiRMnkkcmlIfq/FSr43GrwsDAoMIkd9nZ2YINdLm6uuLkyZNS+a41NDTw3Xff4euvv0ZYWFiNbZOQBSIrl9tYa4OG3GblBIDivLec26wrWFtby/SFCwsLkZiYiKFDhwpSh5UrV0JSQUIINTU1rF69usqE9u+DBrsIQWEY+f+4pFevXvjrr7+QkfFfiOivv/6KwsJCuLm5cfuwStDS0pKZcnoXCwuLGtsmjywQSa+43US8RRPu+3Wp8dGc2yyfd4upVuOaO4YPH45Dhw5h6tSpmDp1KtLS0rBu3ToMHjyY96b14MGD4eDgAAcHB7Rv3x7t2rWDlha3AUIUay0QGencjoxKJNwPnunqcPvjAgBdfelosbycXLnvbaDHbaTZuyGaOjo6GDRokCAhmnPnzkV4eDhSUkrztolEIojFYjg4OMDR0RGurq5o1qxZrZ5BQhYIEnIpb7PlF3L5e5WVq1evYtGiRRg5ciRat26NFy9e4MaNG7h58yY7Yt6zZ08sW7YMzZvXbLN5ErJAJCa94tSejjb3vaIG2pqc2yyfRTMnS/4uhp6BHtfVUQiDBw/GyJEjMWLECKnzV69excqVKzF9+nQcO3YMycnJCAkJgampabWfQYNdhKAwDCP3n6rw9OlTmV0mAMDNzQ0+Pj64c+cODhw4ACMjI+zcubNGz6DBLoHg2oOKeFgO+Cqd2wE5QNYjS0pUR6DyYmlpiVu3bkktYSzD2dkZBw8ehLa2NkaNGoWAgAB8/fXX1X4GeWRCUOqjRx4xYgR+/PFHnD59Wubaw4cPkZ9fmtChdevWePWqZl0w8sgCUcK5J+J+sMtQj/8F9tx/D3WfUaNG4cGDB5g/fz6CgoLg4eEBMzMzxMfHY//+/ezSxdzc3BqPoJOQBUJbi9uvuqiY+8QCqW+4j+wyNZPOu6VKnrY6rFq1Ch988AH8/f3xv//9jz3v6OiIFStWAAD+/vtvtGjRokb2adRaILiefuJDyOmZeZzbbNdWen701Sv5U8Q2bizEIg7hSU1NxcuXL2FiYgJzc3P2fGRkJN6+fYsuXbpU2yZ5ZIEoKCzm1B4fyxhFIv5XAdXHpjVQGtf9119/4cWLF2jatCk6deoEPT3p6TUHB4ca2ychE4JSH9t/KSkpmDhxIh4+fMie09HRgY+PD7766itOwjVJyALBdRbN3DxuExUAgL4u9yuqylNSD5X87bffIj8/H7t27UKrVq3w/PlzXLt2DT/99BPi4uLw448/QlTLxP3URxaIly/TOLXH9eAZANyNe8G5zd6u7aSOk569lvtey+ZmXFdHIXTv3h1LlizBgAEDpM4/evQIo0aNwoQJEzBhwoRaPYPmkQlBqY/zyPn5+TAxMZE5b2VlhUmTJiE0NLTWz5D7tf78+XMMHDiw0uvnzp1j11NOnDgR4eHhFZabNGkSJk+ezB6fPn0ay5cvr7CshYUFzp07J3WuY8eOldZh9+7d6Ny5M3u8bNkynDlzpsKygwcPxqpVq9jjO3fuwNfXt1Lbd+/elToeOHAguw1IeVauXImPP/5Y6hzXg1P5BdwOngGAXWv+PWAxD9k/6zo2Njb4888/0bVrV5lrdnZ2SEpKqvUz5G5aFxcXIzlZdtuTWbNmoWXLlvjuu++goVH6XkhJSWGjVcpjaGgIIyMj9jgnJwdpaRU3OzU0NGSWdz19+pT995w5cxAZGSl1XV1dHbdv34aenh7S0tLw999/4/jx44iIiEB2djZMTU3h6OiIcePGSb0U8vPz2WVmFVE+VjY5ORnFxf+J6fTp0zh+/DjS09NhbW2Nr7/+Wuqlkpb6plLbNaGwiPvpJz5SVzVtKu2JEh7L33y3bm1edSEl4Pz581i4cCE2b96M3r17S107fPgw9u7di8uXL9fqGXJ7ZA0NDZkfc0lJCZ48eQIfHx9WxADY5GLyoKenJzMM/z7K6sAwDB4/fowFCxZg8ODB7HV1dXXW3uXLl7F8+XJ8+umnmDp1KszMzJCYmIiDBw/i0qVLUkLW0dGpMLD9XTIzM6GhoYGGDRtKvWDOnz+PXbt2Yfny5XB2dsbRo0fh6+sr1Uq5E1ux964pTm3k/47lhevdMCqiPg52DRgwAOHh4Zg6dSq6du2K3r17w8zMDI8fP8b+/fvh5eVVtZEqqNVgV3x8PAYOHIjjx4/D0dFR5vqDBw+wYcMGdq+dwYMHY86cOVLD7Q8fPsSKFSsQERGB1q1bY9myZRg5ciROnTqFdu3aydgs4/Hjx/Dw8Kj02Xfu3MHo0aPx9ddfY+TIkTLX37x5I9UyqIzi4mL88ccfCAkJweXLl3H8+HGZeg0bNgx2dnZYuXIle87T0xMfffQR5s6dCwBIfp5a5bOqg4iHDcN1eFjGaGQsnYL2QYL8LzSxdc1T39RFTp48id27d+PJkyfsuX79+mHt2rVoWMvtemo19BkVFQUNDQ3Y2NjIXIuOjsaoUaMwevRoLF26FCkpKZgzZw709fUxbdo0AKUi9vHxwZgxY7Bq1SokJCRg5syZ0NTUhJWVlVzPrkzs69atg4uLS4UiBlCliOPi4hAaGorTp0+juLgYHh4eCAwMlHleYWEhoqKipHYMAEpHKsv3q4n6ExBy4MABODo6wtbWlo2fHjp0KIYOHYoXL14gLS0NzZo1g7ExN1vH1krI0dHRsLa2hra27Pzj0qVL4eXlhdmzZwMobRL7+PjgypUrrJBXrVoFNzc3toy1tTVOnz6NpKQkaGlp4cWLF5g/fz7S0tIgEokwdepUeHp6AigVskQikRpAEIvFCAoKQkJCAiIiIrBly5ZqfZ6MjAycOXMGISEhePjwIXr16oXly5fjww8/rHTSPiMjAxKJRGZU0tTUFK9f/zfVwrUH5SNPdsMGAkR21ZOm9bp16wCUpvWxsrJC+/bt2T+xWCwVmskFtRZyRbuvJyQkICoqChs2bJA6r6mpicLC0kCGZ8+eISwsDGfPnpUqo6WlxXo9kUiExYsXw9bWFmlpafD29oabmxt0dXURFRUFT09PzJo1i723LENhVFQUAFR7Z/hDhw5h27Zt6Ny5M3799ddqfdnlk5wLmfhcmVClaaX3cfv2bURERCAyMhIRERG4efMmTp48CTU1NWhqasLGxoZNxufg4ACxWFyr59VYyAzDICYmBv3795e5Fh8fD01NTbRu3VrmfFmFY2NjoampKbNTe0JCAry9vQEAjRs3RuPGjQEAJiYmMDQ0RGZmJnR1dRETE8OOmJenbMRcV1e3Wp+pbNAuNDQUAwYMQP/+/eHl5YWuXbtCvZKF/MbGxhCJREhNle4Dp6Wl1Shli7z8/eAl5za72HLfJ9U3lD6uLx5ZT08Prq6ucHV1Zc9lZGSw4o6MjMSlS5dw5MgRxW50npiYiOzsbNhVsINfw4YNIZFIUFxczDZJnz9/josXL2L79u0ASr2tRCJBQUEB2zQPCwtDbGxshX3uiIgIMAwDc3NzJCUlISsrq8JnA2BfDuHh4ejbt6/M9fz8/ArXfTZp0gRTpkzBlClT8PfffyM0NBRffvklGjZsiMGDB8PLy0vmxaOlpQV7e3vcuHFD6ll//vmn1N5FXP9+O7fjfmomhYcMIebm0l2O+tJHrghjY2P06tULvXr1Ys+9fv0aERERtbZd48iusuarSCTCgwcP2L9Hjx7ByckJhoaG+O6775CUlISbN2/C19cXHh4ebDJwe3t7aGho4Ntvv0VSUhJ+//13LFmyBABga2sr9ayMjAwsWLCADeCIjIyESCSqdKCrY8eO6NGjB1auXInQ0FA8ffoUjx8/xunTpzFy5EgkJiZW+fmcnZ2xatUq3LhxA/Pnz0dsbCy8vLwQFxcnU3bcuHE4ceIETpw4gYSEBKxZswYvXrzA8OHD5f9C6wmSEkbuv/qAmZmZzNxyTaixRy5rCvj4+Eid79ChA4KCgrBjxw7873//Q1BQEMzMzODj4yMVT9q4cWOsWbMG33//PYKDg9G9e3d88sknCAkJkRpRLiwsxPTp0+Hn5wdnZ2cApX3z1q1bvzdr/86dO7F//37s3buXHTxr0aIF3N3d0aZNG7k/p7a2NgYOHIiBAwciJSWlwmmCAQMGICMjAzt27MCrV68gFosREBAgNdccl8jt9FO7ltw3282M+U8/W589Mp/UmUUTJSUlGDNmDJydnTFnzhwApf3wuXPnonXr1vjyyy8VXMPaceWWrCevDXwImQ8v2MxCup637z+S+14Xp/dPQRL/obBljLdv30Z6ejrs7OyQkZGBPXv2IDk5Gdu2bWPLhIeH4/z587CxscGlS5cAlC4Jq6gPXddp0dSw6kLVgI/EAkX5RZzbLA85ZH5QmJBTU1Px/fffIyUlBaampnB1dcXx48elmtWdO3dGbGysoqrIKZq1XG9aHj4aUkmvuN/wu/xSxDrSAFQ5FCZkT09PNriDqD/Ul+knoaEMIQLBtSfiQxDNzQyqLlRLaLCLH0jIhKCQQ+YHErJAFBTV/SyaQkBNa34gIROCwsd2sIQChJySkoINGzbg+vXryM/PR6tWrfC///2Pzem7cOFChISESN3j5OSEY8eOCV1VTtHW5HgTNx5yUCe/ln/vYnlpYSl9TF1kfhBUyJmZmRgxYgS6du2K3bt3o1GjRkhKSoKBgfQgS8+ePbF27Vr2WFOT+wXvyk4OD+lw7Vo35txmeWj6iR8EFfLu3bvRtGlTKZFWtEO7lpYWzMzkTwRXXFyMdevWITQ0FCKRCJ9++ilSU1ORnZ2NHTt2ACj9Ae3ZswdHjx7F69ev0apVK0ydOhUeHh4AgFu3bmHMmDHYv38/NmzYgISEBNja2mLNmjVSSQ4uX76Mbdu24eHDh2jcuDG8vb0xefJkNtXR1q1bcfLkSaSmpsLIyAgeHh5YunRpjb4vVYT6yPwgqJAvX76MHj16YMaMGbh9+zaaNGmCkSNHysRrh4WFwdXVFQYGBnBxccHs2bMrTCdaxu7du3HmzBmsXbsWVlZWCAwMxKVLl6SSDmzevBm//PILVqxYgVatWuH27duYN28eGjVqJLXXzqZNm7Bw4UI0atQIy5cvx+LFi3H06FEAwPXr1zFv3jwsXboUnTt3RmJiIruX7fTp03HhwgXs378fGzduRNu2bZGamsoGtHD9AzbgIZn84+fy78skL/Y20vHbpGN+EFTISUlJOHLkCMaNG4fJkyfjn3/+werVq6GlpYUhQ4YAAHr16gUPDw9YWFjg2bNn+OGHH/DFF18gODi40iwdhw4dgp+fH7uMcNmyZbh27Rp7/e3bt9i3bx8OHDjAJtyztLREeHg4goKCpIQ8e/Zs9tjPzw9+fn7sUkt/f3/4+fmx66UtLS0xc+ZMbNiwAdOnT8eLFy9gamqKDz74AJqamrCwsKgwn1h9huaR+UFQITMMAwcHB3ZRhJ2dHeLj43HkyBFWyO9m4xeLxXBwcEDv3r1x5coV9OvXT8ZmdnY2UlNTpQQjEolgb2+Pkn9zKMfHx6OgoADjx4+XureoqEhmyeS7cdxlzfu0tDRYWFggKioKERER8Pf3Z8uUranOy8uDh4cHDhw4gI8++gg9e/aEm5sb3N3dpTKMcsVbHuKihZjSoqY1PwgqZDMzM1hbW0uds7KywsWLFyu9p3HjxrCwsJDKPFgRFaXaKf/vXbt2yaTqLe/l3xVdmc2yF0JJSQm+/PLLCl8o2traMDc3x4ULF3Djxg3cvHkTK1euxN69e3Hw4EG8ya44z3dNMdLnflPyRgaVLwvlCtIxPwgqZGdnZzx+/Fjq3JMnT2SS0L9LRkYGXrx4wab8KY++vj5MTU3xzz//sAnhJRIJYmJi2MQD1tbW0NLSwvPnz2u092wZdnZ2ePz48XvzX+vo6KBPnz7o06cPRo4cCU9PTzx48ACA/Lm7VRnyyPwgqJC/+OILjBgxAv7+/vD09MQ///yDY8eOsZk/cnNzsW3bNvTr1w9mZmZITk7Gpk2bYGxsjI8++qhSu6NGjcKuXbvQokULWFlZ4dChQ8jMzGQ9qp6eHsaPH4+1a9eCYRh06tQJOTk5uHv3LnR1ddk+b1VMmzYNkydPhrm5OTw8PKCuro64uDjExcVh9uzZCA4OhkQigZOTExo0aIBTp05BR0cHFhYWyM7htinMx9YrqW/ecm7T1Ew63Wt9yfwhNIIK2dHREdu2bcPGjRuxfft2NG/eHIsXL2b3SSpLGxQaGors7GyYmZmha9eu2LRp03t3o/D19UVqaioWLFgAkUgEHx8f9OjRQ2qrylmzZsHExAS7du3Cs2fPoK+vDzs7O6l9qKqiZ8+e8Pf3x/bt27Fnzx5oaGjAysoKw4YNAwAYGBggICAA69atQ0lJCcRiMfz9/WFsbIzsnFc1/NZUCxrs4oc6kyGES0pKSthlku+my1Uk1dnzSB60OI4UA4AiCff7SVm1bCp1fPzifbnvHdbfievqqCwqEWudnJyMGzduwMXFBYWFhTh8+DCSk5Ol9oRSNLo63O6rlFfI/ag11wNyFUF9ZH5QCSGrq6sjODgY69evB8MwEIvF2Ldvn8wIOaF4VLABWCdQCSGbm5uz0Vd1laJibputDA99TT6mtMqjTF3kGzduIDg4GPfv30dSUhI+//xzLFu2TNHVqhCVEDKhPChT0/ratWuIiYmBi4sLMjO5z2fGJSRkgeB6uqiAh43OmzTif66bUaLlyAsWLMCiRYsAlC6qqcuQkAXidQa3c7TmJtyL7k12Huc2TUyNpI6VySNXtt9XXYSETAiKEulYqSAhC0SLJtwmqM/JK+DUHgBkv+U+WUF5iqsx2vXuJngV8dtvv9W2OioDCZkQFEVOP2VnZ+PVq6oj7CwtLStdMltXISELBNcelI9ljFy3GiqiOn1krj3ur7/+yg5evY/Q0FCZ5a11HRKyQBQVcztcy8cIcwYPg13lF00oso/8ySef4JNPPlFcBXiEhEwICi2a4AcSskBoanA7lZH9lvvBrrhE7nN2tbWykDpWJh0nJycjIiICAJCXl4fExERcuHABANikjXUFEjIhKMo0/XTr1i2pPvX169dx/fp1AEBcHLf7XdcWErJAFHIcicVHfq3ujpZVF6olyhQQokx9ahKyQJTPKVYXEWI7FyXSsVJBQiYEpToBIYT8kJAFQkPE7WBXA23ut9H5Jz6Fc5u9ZaafSMh8QEImBIUcMj+QkAWC6/2R+cCyiUHVhWoJeWR+ICETgsJDFl8CJGTB4HplkbYh9/91XO/hXBHUtOYHErJAJKZkc2rP1FCXU3sAPwsxykNNa34gIROCQh6ZH0jIAtG9veyG7rUhK5f7HNQiAVLbKFNklzJBQiYERYDgsXoJCVkgcvO4HezS0uQ+1vplWi7nNtuVOyaPzA8kZCVFxHGkGADkCjLYxfsj6iUkZEJQaLCLH0jISkp6JvdpedpbV7yZPJfQ9BM/kJAJQSGPzA8kZIH4I5Lb/ZFd7Zpwak8oSMj8QEIWCP0G3H7VfIz+ZudynwesPDRqzQ8kZEJQSMf8QEIWCLtWjTi1p6+rzak9AMjM4T5arDwcbxNN/AsJmRAUGrXmBxKyksLHksOkV9yu0AIAJzvpYxrs4gcSskCkcTzvy8eODbYtTTi3WR4SMj+QkAlBoZY1P5CQBYLrRQ58CMJIvwH3RstB00/8QEImBIWa1vxAQhYIrrdV1WzI/eqnpJRMzm2amBpJHZOQ+YGELBD6ulqc2uMjv5Zta/4XTZCQ+YGETAgKdZH5gYSspNxLSOPcZvPGhpzb1DPQkzqmvZ/4gYRMCArpmB9IyALBdQBH66b6nNoD+MkDVh4SMj+QkAlBISHzAwlZICQc/4L1GnC/raq6Ov+bsdNgFz+QkAWC63S4mhrcN4PV1PgXMnlkfiAhE4JCQuYHErJAvMnl1iObGXIfF/06I4dzm0bG0nsuk5D5gYRMCArtj8wPJGSBMDHQ4dSehAdFLP8plnObPy21kDrmOOSc+BcSskBwvWiiZVODqgtVk86thVjGyPsj6iUkZEJQJCRkXiAhCwTXHvTpyyxO7QGAtble1YVqCXlkfiAhE4JCQuYHErJAPHnB7aJ9mxbcJ8o7e/Mx5zbLQ0LmBxKyQLzO5Db5e9Gj15zaA4ARH5Xflpx7qI/MDyRkQlCUxSNLJBL8+OOPuHr1KuLj4yGRSCAWizF9+nS4uroqunoykJAFopE+t1u8pGZxv73L5pP/cG5zpW9PqWNl8cj5+fnYtWsXhgwZggkTJkBDQwMhISEYN24cdu7cCXd3d0VXUQoSMiEoRUoSEKKjo4PffvsNhob/ZU3p0aMHnjx5gh9//JGEXF95/YZbD/q2sJhTewDg2o7/nSaUxSOLRCIpEQOlq8PatWuH8PBwBdWqckjIAlEk4dYVZb3lXshGetzv8FgeSQn/SyX5oqSkBHfv3oW1tbWiqyIDCZkQlOp45D59+rz3+m+//VbL2lSPgwcP4vHjx1i1apWgz5UHNYb2uSTqKFwLOTs7G69evaqynKWlJbS0pPOQh4WFYfz48RgzZgzmz59frecKAQmZqDcEBwdj0aJFVZYLDQ2Fra0texwbG4tRo0ahR48e2LRpkyCZVKoLCZkg3kNiYiJGjhwJKysr7NmzR8ZT1xVIyARRCa9fv8aIESOgp6eHQ4cOQU+P/0UlNYWETBAVkJ+fj88++wyJiYnYsGEDTE1Npa536NBBMRWrBBIyQVTAs2fP3jvYFhcXJ2BtqoaETBAqAPeb7BIEITgkZIJQAUjIBKECkJAJQgUgIROECkBCJggVgIRMECoACZkgVAASMkGoACRkglABSMgEoQKQkAlCBSAh1xEkEglKeNwFPCEhAdu2bePNPqFYSMgCcu/ePdy8eVPq3NmzZzFo0CA4OTnByckJ3t7euHz5MufPjo+Px/bt2+UuX1RUhHv37uHOnTvsCyY3Nxf79u3DihUr8OOPPyIzk9v9rIiaQ1k0BWT16tXw8PBgtxw5dOgQVq9eDXd3dwwbNgwMw+DmzZuYNm0a1q9fj48//lgh9Xz16hV8fX3x4MEDMAwDBwcHBAQEYOzYsXj06BEaN26MlJQUHDx4ECdPnkSjRo0UUk/iP8gjC0hCQgLs7e3Z4x9//BFjx47Fzp078cUXX2Ds2LHYtWsXPv/8c+zatUth9fzhhx+QnZ2NvXv34uTJk9DX18ekSZPAMAyuXLmCy5cv45dffoGmpqZC60n8BwlZQEQiEYqL/0ssn5KSgt69e8uU6927NxITE4WsmhR//vknpk+fjg8++AD29vZYunQpIiIiMGnSJDblTbNmzTBu3Dhcv35dYfUk/oOa1gLi4uKC06dPo2fP0o3N2rZti/v376NLly5S5e7fv4+mTZvKZfPNmzdylcvNzZW7nqmpqWjRogV7XPbvd88BgJWVFV68eCG3XYI/SMgCMmfOHIwYMQLz5s3D6NGjMXfuXMybNw9ZWVno2rUrgFJvePDgQbmToHfr1k2uPMsMw8idj9nQ0BBpaWnssUgkgrOzMwwMDKTKZWdn19n0sPUNytklMLGxsVixYgXu3bsHNTU1lH39Zf82NDTE1KlT8cUXX8hlLzg4uFoJ0729vassM2HCBFhbW2Px4sXvLbd582b89ddfOHr0qNzPJ/iBhKwgEhIScP/+faSmpqKkpASGhoawtrZGx44doampqdC6RUVFISsrq8oNvZcvXw5HR0cMHTpUoJoRlUFCVmEkEgnU1NSgrk5jmqoO9ZHrCL///jsSEhJgamqKvn37omHDhnLdd+/ePeTl5Ul5z7Nnz8Lf3x9PnjyBmpoa2rRpgy+//LLCEXJCNSCPLCAHDhzAlStXsG/fPvacRCLBuHHjcPv2bba/3KxZMwQFBcnsblARn376KTw8PDBx4kQA0kEm3bp1Y4NMrl27xnmQSWRkJA4fPoy1a9dyZpOoGdTmEpCLFy/KbJJ95MgRhIWFwdvbG6dPn8YPP/yA3Nxc7N69Wy6bigwySU5ORmhoKKc2iZpBTWsBefLkCUaNGiV17ueff4apqSm++eYbiEQiiMViJCcn4/jx43JtAVqdIJOgoCC56hkVFSVXuaSkJLnKEfxDQhaQnJwcmJmZsceFhYW4f/8+PD09IRKJ2PN2dnZ4+fKlXDb5CDIZOnQo53PTBL+QkAXE3Nwcjx8/houLCwDg77//RnFxsYzoiouL5Q604CPIRE9PD927d8fnn3/+3nJhYWHVWlFF8AcJWUDc3Nzg7+8Pa2trmJmZYfv27dDS0pJpCv/zzz9o3ry5XDbbtm2LQ4cOYcWKFfDx8WEDS3bv3o09e/awQSZfffUVRo8eLZdNR0dHpKeny7xgypORkSGXPYJ/SMgCMnXqVNy8eZPtJ6upqWHRokUwMTFhy0gkEoSEhMDDw0Nuu+3atcPRo0c5CzLp1KkTjh07VmW5Ro0aoXPnznLbJfiDpp8Epri4GGFhYcjKyoKdnZ3MQoTMzEz89ddfcHJykrtPSxAkZAFZtGgRpk6dCktLS0GeV9MgE0L5ICELSLt27XDs2DE4OjpyZpOPIJP3QS+HugkFhCg5fASZHDhwAOPGjZM6J5FIMGbMGEydOhXfffcdFi5ciI8//hipqamcfRai5pCQlZwnT57A2dlZ6ty7QSZisRj9+/eHn58frl27JpdNPl4OBL/QqLXArF+/Hvr6+lWWU1NTw86dO6ssx0eQCR8RaAS/kJAFJi8vj9NlhXwEmfDxciD4hYQsMCtWrOB0sIuPIBM+Xg4Ev5CQlRw+gkz4eDkQ/EJCVnKMjIwQEhLy3iCTnJwcfPXVV3BycpLLJl8RaAR/0DyygIwePRorVqyQGRGuDXwFmVAEmnJBQlZy+AgyEToCjag91LQWkMmTJ8tdVt7pJz4ICQnBiBEjSMhKBAlZQOTZ7SE3NxfR0dG0YJ+oFiRkATl48GCl13JycnDw4EHs378fWlpa8PHxkdsu10EmhPJBQlYwOTk5CAwMxIEDB1BQUIBhw4bB19cXjRs3ltsG10EmAL0clA0SsoLIycnB/v37cfDgQRQUFOCzzz7DxIkTpSKq5IXrIBOAn5cDwR8kZIHJzs7GgQMHEBgYiKKiIgwfPhwTJ06UmqOtC/DxciD4g4QsIFu2bMHBgwchkUgwcuRIjB8/Ho0aNVJ0tQgVgIQsIDt27ICamhqcnJwQHx//3t0O5e17uri40OJ+goQsJGWLEIDqbTz+Pt43El5T6OWgfFBkl5KjLEEmBL+QR1Zy+AgyoZeD8kFCFhB591Qq493N2SqDjyATikBTPqhpLSDt2rWr1p5KMTExNXoOF0Em77Nd9nLIy8uDj48Pli5dWmu7RO0gjywggYGBvNrnMsikItt8vRyI2kMeWQXgM8iEz5cDwR3kkZUcvoJMlCUCjSiFPLKSU9bvdnJygpGR0XvLyjvCTBFoygcJWcmRd6vUMuQJIOHj5UDwCzWtlRy+IrvK4CoCjeAX8sgEoQKQR1Zy+AgyIZQP8sgC4uzsjMDAQDg4OKBjx47vDQ5RU1NDeHh4lTb5CDKhl4PyQR5ZQMaPH8/Ov44fP56T8EY+gkyGDh0qSAQawR3kkQkZwsLCqlW+/J5QhPCQkOsQeXl5ePXqFVq0aEGLEYhqQdnVFMTevXuxbds29vjOnTvo1asXPDw80K9fPyQmJiqwdoSyQUJWEMePH0eTJk3Y4zVr1qBNmzbYsWMHjI2NsXHjRgXWjlA2aLBLQbx8+RItW7YEAKSkpCA6OhqHDh1C586dIZFIsGLFCsVWkFAqyCMrCG1tbeTk5AAAbt68CV1dXXTs2BEAoK+vj+zsbEVWj1AyyCMrCEdHRwQEBEBdXR179+5Fr169IBKJAACJiYlSzW6CqAoatVYQ8fHxmDx5Mp49ewYLCwv8+OOPaNWqFYD/5pvXr19fpR0+gkwI5YM8soJo06YNLl26hIyMDBgbG0tdW7BggdwL9/kIMqGXg/JBHpmQYdu2bRg2bBiaNGmCrVu3VvlymD59ukA1IyqDhKziUJBJ/YBGrVUIoYJM8vLy8PTpU5APqDuQkFUIPoJMKAJNOSAhqxAVBZnMnTsX7u7u8PPzw507d6ptkyLQlAMatVYh+AgyoQg05YCErELwEWRCEWjKATWtVYgFCxYgNTUVkydPRm5uLmbNmsVe+/nnn1kBVoeyl8OVK1coAq0OQ9NPKkhFQSZxcXEwMzOrdn5qriLQCH4hIRNyweXLgeAeEjJBqADURyYIFYCETBAqAAmZIFQAEjJBqAAkZIJQAUjIBKECkJAJQgUgIROECvB/K34VbGVpJIYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 100x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(1,3))\n",
    "\n",
    "feature = 'log2FoldChange'\n",
    "\n",
    "genes_of_interest = {'JUNB':'JUNB'}\n",
    "\n",
    "data = intersection.loc[abs(intersection['RNAseq_cat_1'])+abs(intersection['RNAseq_cat_2'])+abs(intersection['RNAseq_cat_3'])>=3].reset_index(drop=True)\n",
    "data['av_cat'] =((data['log2FoldChange_1']>0).astype('int')*2-1)+((data['log2FoldChange_2']>0).astype('int')*2-1)+((data['log2FoldChange_3']>0).astype('int')*2-1)\n",
    "data['av_effect'] = data[[feature+'_1',feature+'_2',feature+'_3']].median(1)\n",
    "data = data.sort_values(['av_cat','av_effect'],ascending=[False,False]).reset_index(drop=True)\n",
    "\n",
    "data['all_up'] = ((data['log2FoldChange_1']>0).astype('int')+(data['log2FoldChange_2']>0).astype('int')+(data['log2FoldChange_3']>0).astype('int')==3).astype('int')\n",
    "data['all_down'] = ((data['log2FoldChange_1']<0).astype('int')+(data['log2FoldChange_2']<0).astype('int')+(data['log2FoldChange_3']<0).astype('int')==3).astype('int')\n",
    "\n",
    "data_to_show = data.loc[data['gene_name'].isin(genes_of_interest)]\n",
    "\n",
    "ax = sns.heatmap(data[[feature+'_1',feature+'_2',feature+'_3']],cbar_kws={'label': '$log_2FC$','aspect':20},vmin=-2,vmax=2,center=0,cmap=sns.color_palette('vlag',as_cmap=True))\n",
    "ax.set(xticklabels=experiment_labels,ylabel='',yticks=[],title='all\\nthree experiments\\n#='+str(len(data)))\n",
    "\n",
    "# for index, row in data_to_show.iterrows():\n",
    "#     ax.text(0,index,'< '+genes_of_interest[row['gene_name']],ha='left',va='center',size=10)\n",
    "\n",
    "y_pos = np.max(list(data.loc[data['all_up']==1].index))\n",
    "ax.text(0,y_pos,'_ _ _ _ _ _ _ ',ha='right',va='bottom',size=10)\n",
    "ax.text(0,y_pos*0.9,'$Log_2FC>0$\\n'+str(len(data.loc[data['all_up']==1]))+' genes',ha='right',va='bottom',size=10)\n",
    "\n",
    "y_pos = np.min(list(data.loc[data['all_down']==1].index))\n",
    "ax.text(0,y_pos,'_ _ _ _ _ _ _ ',ha='right',va='top',size=10)\n",
    "ax.text(0,y_pos*1.1,'$Log_2FC<0$\\n'+str(len(data.loc[data['all_down']==1]))+' genes',ha='right',va='top',size=10)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_6L_vs_11_heatmap.3.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_6L_vs_11_heatmap.3.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 505,
   "id": "636cc6ba-8918-4af1-899c-7f5092298940",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = intersection.loc[abs(intersection['RNAseq_cat_1'])+abs(intersection['RNAseq_cat_2'])+abs(intersection['RNAseq_cat_3'])>=2].reset_index(drop=True)\n",
    "data['all_up'] = ((data['log2FoldChange_1']>0).astype('int')+(data['log2FoldChange_2']>0).astype('int')+(data['log2FoldChange_3']>0).astype('int')==3).astype('int')\n",
    "data['all_down'] = ((data['log2FoldChange_1']<0).astype('int')+(data['log2FoldChange_2']<0).astype('int')+(data['log2FoldChange_3']<0).astype('int')==3).astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 506,
   "id": "d507cbd5-2281-4c47-b43f-4c1275e41004",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(198, 362)"
      ]
     },
     "execution_count": 506,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data.loc[data['all_up']==1]),len(data.loc[data['all_down']==1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 508,
   "id": "a2939e18-d0f0-4866-af50-1637b6b66fb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_up = data.loc[data['all_up']==1][['gene_name']].reset_index(drop=True)\n",
    "all_down = data.loc[data['all_down']==1][['gene_name']].reset_index(drop=True)\n",
    "background = intersection.loc[~intersection['gene_name'].isin(list(all_up['gene_name'])+list(all_down['gene_name']))][['gene_name']].reset_index(drop=True)\n",
    "\n",
    "all_up.to_csv(subdirs['tables_dir']+'GO_enrichment/all_up.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "all_down.to_csv(subdirs['tables_dir']+'GO_enrichment/all_down.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "background.to_csv(subdirs['tables_dir']+'GO_enrichment/background.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 532,
   "id": "f48fffa7-78cc-4699-a1e0-ad5c8051a6b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 150x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show GO terms\n",
    "ALL_up = pd.read_csv(subdirs['tables_dir']+'GO_enrichment/ALL_up;GOPROCESS.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "ALL_down = pd.read_csv(subdirs['tables_dir']+'GO_enrichment/ALL_down;GOPROCESS.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "ALL_up['Description'] = ALL_up['Description']+', '+ALL_up['b'].astype('str')\n",
    "ALL_down['Description'] = ALL_down['Description']+', '+ALL_down['b'].astype('str')\n",
    "\n",
    "ALL_up['score'] = (-1)*np.log10(ALL_up['FDR q-value'])\n",
    "ALL_down['score'] = (-1)*np.log10(ALL_down['FDR q-value'])\n",
    "\n",
    "x_feature,y_feature ='score','Description'\n",
    "x_label,y_label = '-$log_{10}FDR$ for GO term',''\n",
    "\n",
    "ALL_down = ALL_down.sort_values(x_feature,ascending=False).head(10)\n",
    "ALL_up = ALL_up.sort_values(x_feature,ascending=False).head(10)\n",
    "colors = ['skyblue','green']\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(2, 1, sharey=False, sharex=True, figsize=(1.5,4))\n",
    "\n",
    "j=0\n",
    "ax = sns.barplot(ax=axes[j],data=ALL_up,x=x_feature,y=y_feature,color=colors[j])\n",
    "# ax.yaxis.tick_right()\n",
    "ax.set(xlabel = x_label,ylabel = y_label,title='genes with $log_2FC>0$')\n",
    "\n",
    "j=1\n",
    "ax = sns.barplot(ax=axes[j],data=ALL_down,x=x_feature,y=y_feature,color=colors[j])\n",
    "ax.set(xlabel = x_label,ylabel = y_label,title='genes with $log_2FC<0$')\n",
    "\n",
    "fig.tight_layout(pad=0.001)\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'top_GO_terms.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'top_GO_terms.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 535,
   "id": "f1ae1c88-c36d-42b4-a924-3405a1feec01",
   "metadata": {},
   "outputs": [],
   "source": [
    "intersection.to_csv(subdirs['tables_dir']+'Deseq2/intersection_of_three_experiments.tsv',sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7713602e-befd-4715-9fa6-960ccdf62384",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "intersection['t']=1\n",
    "gr = intersection.groupby(['RNAseq_cat_1','RNAseq_cat_3']).agg({'t':np.sum}).reset_index()\n",
    "gr1 = gr.loc[(gr['RNAseq_cat_1']!=0)|(gr['RNAseq_cat_3']!=0)].reset_index(drop=True)\n",
    "gr1 = pd.pivot_table(gr1,index = 'RNAseq_cat_1',columns='RNAseq_cat_3')\n",
    "gr1.columns = gr1.columns.droplevel()\n",
    "gr1 = gr1.sort_index(ascending=False)\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3))\n",
    "\n",
    "ax = sns.heatmap(gr1,cbar_kws={'label': '# genes'},vmin=5,vmax=500,center=0,cmap=sns.color_palette('vlag',as_cmap=True),annot=True, fmt=\".0f\")\n",
    "ax.set(xlabel='si INTS13', ylabel='si INTS6')\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_13_heatmap.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_13_heatmap.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7208c229-cbbf-492f-89d8-e4da08b4effc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "intersection['t']=1\n",
    "gr = intersection.groupby(['RNAseq_cat_2','RNAseq_cat_3']).agg({'t':np.sum}).reset_index()\n",
    "gr1 = gr.loc[(gr['RNAseq_cat_2']!=0)|(gr['RNAseq_cat_3']!=0)].reset_index(drop=True)\n",
    "gr1 = pd.pivot_table(gr1,index = 'RNAseq_cat_2',columns='RNAseq_cat_3')\n",
    "gr1.columns = gr1.columns.droplevel()\n",
    "gr1 = gr1.sort_index(ascending=False)\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3))\n",
    "\n",
    "ax = sns.heatmap(gr1,cbar_kws={'label': '# genes'},vmin=5,vmax=500,center=0,cmap=sns.color_palette('vlag',as_cmap=True),annot=True, fmt=\".0f\")\n",
    "ax.set(xlabel='si INTS13', ylabel='si INTS6L')\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6L_vs_13_heatmap.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6L_vs_13_heatmap.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "72392d1a-afa8-4389-84a4-b00a847a2247",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "intersection['t']=1\n",
    "gr = intersection.groupby(['RNAseq_cat_1','RNAseq_cat_2']).agg({'t':np.sum}).reset_index()\n",
    "gr1 = gr.loc[(gr['RNAseq_cat_1']!=0)|(gr['RNAseq_cat_2']!=0)].reset_index(drop=True)\n",
    "gr1 = pd.pivot_table(gr1,index = 'RNAseq_cat_1',columns='RNAseq_cat_2')\n",
    "gr1.columns = gr1.columns.droplevel()\n",
    "gr1 = gr1.sort_index(ascending=False)\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3))\n",
    "\n",
    "ax = sns.heatmap(gr1,cbar_kws={'label': '# genes'},vmin=5,vmax=500,center=0,cmap=sns.color_palette('vlag',as_cmap=True),annot=True, fmt=\".0f\")\n",
    "ax.set(xlabel='INTS6L', ylabel='INTS6')\n",
    "ax.tick_params(bottom=True,left=True)\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_6L_heatmap.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/'+'INTS6_vs_6L_heatmap.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "da52bd05-024c-4d16-8a15-081a729334ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 6L vs 6 vs 13 - downregulation\n",
    "\n",
    "from matplotlib_venn import venn3,venn3_circles\n",
    "from matplotlib_venn import venn2,venn2_circles\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(6,6))\n",
    "\n",
    "labels_to_show = ['INTS6','INTS6L','INTS13']\n",
    "\n",
    "ax = sns.scatterplot(data = None)\n",
    "ax.set(title='upregulated genes')\n",
    "\n",
    "gene_lists = []\n",
    "for label in ['RNAseq_cat_1','RNAseq_cat_2','RNAseq_cat_3']:\n",
    "    gene_list = set(list(intersection.loc[intersection[label]==1]['gene_name']))\n",
    "    gene_lists.append(gene_list)\n",
    "\n",
    "v = venn3(gene_lists,set_labels=labels_to_show,set_colors=['skyblue']*3,ax=ax,alpha=0.5)\n",
    "c = venn3_circles(gene_lists,color='black',linewidth=1,ax=ax)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/Vienn_Diagram_upregulate.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/Vienn_Diagram_upregulate.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "646caa0b-a03e-4141-a694-1291db1d8f2b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 6L vs 6 vs 13 - upregulation\n",
    "\n",
    "from matplotlib_venn import venn3,venn3_circles\n",
    "from matplotlib_venn import venn2,venn2_circles\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(6,6))\n",
    "\n",
    "labels_to_show = ['INTS6','INTS6L','INTS13']\n",
    "\n",
    "ax = sns.scatterplot(data = None)\n",
    "ax.set(title='downregulated genes')\n",
    "\n",
    "gene_lists = []\n",
    "for label in ['RNAseq_cat_1','RNAseq_cat_2','RNAseq_cat_3']:\n",
    "    gene_list = set(list(intersection.loc[intersection[label]==-1]['gene_name']))\n",
    "    gene_lists.append(gene_list)\n",
    "\n",
    "v = venn3(gene_lists,set_labels=labels_to_show,set_colors=['green']*3,ax=ax,alpha=0.5)\n",
    "c = venn3_circles(gene_lists,color='black',linewidth=1,ax=ax)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/Vienn_Diagram_downregulate.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/Vienn_Diagram_downregulate.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "a2c71e50-5664-4b17-8f68-e5e9c6b39c5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# downregulation\n",
    "data = intersection.copy()\n",
    "\n",
    "targets_6_specific = data.loc[(data['RNAseq_cat_1']==-1)&(data['RNAseq_cat_2']!=-1)&(data['RNAseq_cat_3']!=-1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_specific = data.loc[(data['RNAseq_cat_1']!=-1)&(data['RNAseq_cat_2']==-1)&(data['RNAseq_cat_3']!=-1)][['gene_name']].reset_index(drop=True)\n",
    "targets_13_specific = data.loc[(data['RNAseq_cat_1']!=-1)&(data['RNAseq_cat_2']!=-1)&(data['RNAseq_cat_3']==-1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6_13_specific = data.loc[(data['RNAseq_cat_1']==-1)&(data['RNAseq_cat_2']!=-1)&(data['RNAseq_cat_3']==-1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_13_specific = data.loc[(data['RNAseq_cat_1']!=-1)&(data['RNAseq_cat_2']==-1)&(data['RNAseq_cat_3']==-1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_6_specific = data.loc[(data['RNAseq_cat_1']==-1)&(data['RNAseq_cat_2']==-1)&(data['RNAseq_cat_3']!=-1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_6_13_specific = data.loc[(data['RNAseq_cat_1']==-1)&(data['RNAseq_cat_2']==-1)&(data['RNAseq_cat_3']==-1)][['gene_name']].reset_index(drop=True)\n",
    "background = data[['gene_name']].reset_index(drop=True)\n",
    "\n",
    "targets_6_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/down.6_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/down.6L_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_13_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/down.13_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6_13_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/down.6_13_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_13_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/down.6L_13_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_6_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/down.6L_6_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_6_13_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/down.6L_6_13_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "background.to_csv(subdirs['tables_dir']+'GO_enrichment/down.background.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "3d7f554b-446d-43a0-b3c5-0d09ea370773",
   "metadata": {},
   "outputs": [],
   "source": [
    "# upregulation\n",
    "data = intersection.copy()\n",
    "\n",
    "targets_6_specific = data.loc[(data['RNAseq_cat_1']==1)&(data['RNAseq_cat_2']!=1)&(data['RNAseq_cat_3']!=1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_specific = data.loc[(data['RNAseq_cat_1']!=1)&(data['RNAseq_cat_2']==1)&(data['RNAseq_cat_3']!=1)][['gene_name']].reset_index(drop=True)\n",
    "targets_13_specific = data.loc[(data['RNAseq_cat_1']!=1)&(data['RNAseq_cat_2']!=1)&(data['RNAseq_cat_3']==1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6_13_specific = data.loc[(data['RNAseq_cat_1']==1)&(data['RNAseq_cat_2']!=1)&(data['RNAseq_cat_3']==1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_13_specific = data.loc[(data['RNAseq_cat_1']!=1)&(data['RNAseq_cat_2']==1)&(data['RNAseq_cat_3']==1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_6_specific = data.loc[(data['RNAseq_cat_1']==1)&(data['RNAseq_cat_2']==1)&(data['RNAseq_cat_3']!=1)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_6_13_specific = data.loc[(data['RNAseq_cat_1']==1)&(data['RNAseq_cat_2']==1)&(data['RNAseq_cat_3']==1)][['gene_name']].reset_index(drop=True)\n",
    "background = data[['gene_name']].reset_index(drop=True)\n",
    "\n",
    "targets_6_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/up.6_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/up.6L_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_13_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/up.13_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6_13_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/up.6_13_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_13_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/up.6L_13_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_6_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/up.6L_6_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_6_13_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/up.6L_6_13_spec.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "background.to_csv(subdirs['tables_dir']+'GO_enrichment/up.background.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d444d42-2dcc-4312-96aa-e8f6bf7b0421",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf5e0087-aba2-49c3-8b5a-b93a487972b1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4453a9b1-7ab5-4fcb-8b51-95bafc3cc0c0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92214a3d-dff6-4f16-8219-968d7e4ff430",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08384e34-590e-4536-a2aa-067894a1709c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7003d9a3-a775-4c68-bd8d-5dfb881d36b2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1766af77-619d-45d2-bb81-caa2755b687a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 6L vs 6 - downregulation\n",
    "data = intersection.copy()\n",
    "\n",
    "targets_6_specific = data.loc[(data['RNAseq_cat_1']==-1)&(data['RNAseq_cat_2']==0)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_specific = data.loc[(data['RNAseq_cat_1']==0)&(data['RNAseq_cat_2']==-1)][['gene_name']].reset_index(drop=True)\n",
    "targets_common = data.loc[(data['RNAseq_cat_1']==-1)&(data['RNAseq_cat_2']==-1)][['gene_name']].reset_index(drop=True)\n",
    "background = data.loc[~data['gene_name'].isin(list(targets_6_specific['gene_name'])+list(targets_6L_specific['gene_name'])+list(targets_common['gene_name']))][['gene_name']].reset_index(drop=True)\n",
    "\n",
    "targets_6_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/6_6L.down.6_specific.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/6_6L.down.6L_specific.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_common.to_csv(subdirs['tables_dir']+'GO_enrichment/6_6L.down.common.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "background.to_csv(subdirs['tables_dir']+'GO_enrichment/6_6L.down.background.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a58c0193-181a-4963-a61f-0eec7f22e662",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 6L vs 6 - upregulation\n",
    "data = intersection.copy()\n",
    "\n",
    "targets_6_specific = data.loc[(data['RNAseq_cat_1']==1)&(data['RNAseq_cat_2']==0)][['gene_name']].reset_index(drop=True)\n",
    "targets_6L_specific = data.loc[(data['RNAseq_cat_1']==0)&(data['RNAseq_cat_2']==1)][['gene_name']].reset_index(drop=True)\n",
    "targets_common = data.loc[(data['RNAseq_cat_1']==1)&(data['RNAseq_cat_2']==1)][['gene_name']].reset_index(drop=True)\n",
    "background = data.loc[~data['gene_name'].isin(list(targets_6_specific['gene_name'])+list(targets_6L_specific['gene_name'])+list(targets_common['gene_name']))][['gene_name']].reset_index(drop=True)\n",
    "\n",
    "targets_6_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/6_6L.up.6_specific.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_6L_specific.to_csv(subdirs['tables_dir']+'GO_enrichment/6_6L.up.6L_specific.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "targets_common.to_csv(subdirs['tables_dir']+'GO_enrichment/6_6L.up.common.targets.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)\n",
    "background.to_csv(subdirs['tables_dir']+'GO_enrichment/6_6L.up.background.tsv',sep=str('\\t'),header=False,index=None,quoting=csv.QUOTE_NONE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d8a10cc2-0437-4974-9bfa-697443916730",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55984dfa-0957-4f34-afb9-35750e390f5c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60d3eb58-8bde-410b-ae74-8671e0af87af",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "379c0b8a-b6c1-4800-85d3-6579fa6567eb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51e9ec25-7862-4cce-a304-2861264cb1a3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "540c7fef-2303-4141-a420-12c174043c1b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ab2c4d2d-40b0-4266-bbec-aaca9f6b9400",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6cf0c689-a60c-443d-97f1-834386b15b48",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e60b84e-4fb3-4d5a-9a14-774467956a9a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f534b2f9-6cc0-4b25-9f2c-2862e802e6f8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1a3f7a3-d0ff-4106-9233-fbc0e3c7dac1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "902402bc-3cb7-46ae-9bf7-81dfe85f363e",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Run Deseq comparisons, but for TSS regions only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 442,
   "id": "22d98b4a-0437-4e78-8617-400e2b71b087",
   "metadata": {},
   "outputs": [],
   "source": [
    "exper_RNAseq_fastq_file_paths = pd.read_csv(subdirs['temp_dir']+\"\"\"exper_RNAseq_fastq_file_paths.tsv\"\"\",delimiter=\"\\t\",index_col=None,header=None)\n",
    "exper_RNAseq_fastq_file_paths.columns = ['path']\n",
    "exper_RNAseq_fastq_file_paths['name'] = exper_RNAseq_fastq_file_paths.apply(lambda x:x['path'].split('/')[-1][:-8],1)\n",
    "experimental_samples = exper_RNAseq_fastq_file_paths.drop_duplicates('name').reset_index(drop=True)\n",
    "experimental_samples['replicate'] = experimental_samples.apply(lambda x:x['name'].split('_')[0],1)\n",
    "\n",
    "mouse_replicates = ['A12','A13','A14','A15','A18','A19']\n",
    "human_replicates = list('A'+pd.Series(range(1,10)).astype('str'))\n",
    "\n",
    "experimental_samples = experimental_samples.loc[experimental_samples['replicate'].isin(mouse_replicates)].reset_index(drop=True).drop('path',1)\n",
    "condition_map = {'A12':'si_CTRL','A13':'si_Ints11','A14':'si_CTRL','A15':'si_Ints11','A18':'si_CTRL','A19':'si_Ints11'}\n",
    "experimental_samples['condition'] = experimental_samples['replicate'].map(condition_map)\n",
    "samples_to_analyze_df = experimental_samples[['name','condition']]\n",
    "samples_to_analyze_df['batch'] = 'in-house'\n",
    "\n",
    "# public \n",
    "public_RNAseq_samples = pd.read_csv(subdirs['metadata_dir']+'public_RNAseq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "public_RNAseq_samples = public_RNAseq_samples.loc[public_RNAseq_samples['condition_name'].isin(['INTS11_si','siNT'])].reset_index(drop=True)\n",
    "condition_map = {'INTS11_si':'si_Ints11','siNT':'si_CTRL'}\n",
    "public_RNAseq_samples['condition'] = public_RNAseq_samples['condition_name'].map(condition_map)\n",
    "public_RNAseq_samples['batch'] = 'public'\n",
    "\n",
    "samples_to_analyze_df = pd.concat([samples_to_analyze_df,public_RNAseq_samples[['name','condition','batch']]]).reset_index(drop=True)\n",
    "samples_to_analyze_df = samples_to_analyze_df.rename(columns = {'name':'sample'})\n",
    "samples_to_analyze_df['organism'] = 'mouse'\n",
    "\n",
    "plot_specification = samples_to_analyze_df[['condition']].drop_duplicates().reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "id": "669892e9-d50b-4b39-b526-7f49c590857c",
   "metadata": {},
   "outputs": [],
   "source": [
    "organisms = list(samples_to_analyze_df['organism'].unique())\n",
    "cl = []\n",
    "for organism in organisms:\n",
    "    enriched_gtf = pd.read_csv(file_paths[organism+'_enriched_annotation_file'],delimiter=\"\\t\",\n",
    "                                       index_col=None,header=None,usecols = [0])\n",
    "    chromosome_list =  list(enriched_gtf[0].unique())\n",
    "    cl.append([organism,' '.join(chromosome_list)])\n",
    "cl = pd.DataFrame(cl,columns=['organism','chromosomes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "id": "c28c413f-e589-4304-802c-6e04f8360744",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mouse, chr1 done\n",
      "mouse, chr2 done\n",
      "mouse, chr3 done\n",
      "mouse, chr4 done\n",
      "mouse, chr5 done\n",
      "mouse, chr6 done\n",
      "mouse, chr7 done\n",
      "mouse, chr8 done\n",
      "mouse, chr9 done\n",
      "mouse, chr10 done\n",
      "mouse, chr11 done\n",
      "mouse, chr12 done\n",
      "mouse, chr13 done\n",
      "mouse, chr14 done\n",
      "mouse, chr15 done\n",
      "mouse, chr16 done\n",
      "mouse, chr17 done\n",
      "mouse, chr18 done\n",
      "mouse, chr19 done\n",
      "mouse, chrX done\n",
      "mouse, chrY done\n",
      "mouse, chrM done\n"
     ]
    }
   ],
   "source": [
    "counts = {}\n",
    "for index1,row1 in cl.iterrows():\n",
    "    organism = row1['organism']\n",
    "    chromosomes = row1['chromosomes'].split(' ')\n",
    "    a1 = []\n",
    "    for chromosome in chromosomes:\n",
    "        i=0\n",
    "        a = []\n",
    "        for index,row in samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism].iterrows():\n",
    "            sample = row['sample']\n",
    "            file_path = subdirs['wf_output_dir']+'samples/'+sample+'/segment_counts_all/sel_TSSs/'+sample+'.'+chromosome+'.wd_counts.tsv'\n",
    "            if i==0:\n",
    "                tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,usecols = [0,3,4,5])\n",
    "            else:\n",
    "                tmp = pd.read_csv(file_path,delimiter=\"\\t\",index_col=None,header=0,usecols=[5])\n",
    "            tmp = tmp.rename(columns = {'uniquely_mapped;0':sample})\n",
    "            a.append(tmp)\n",
    "            i=i+1\n",
    "        a = pd.concat(a,axis=1)\n",
    "        a1.append(a)\n",
    "        print(organism+', '+chromosome+' done')\n",
    "    a1 = pd.concat(a1).reset_index(drop=True)\n",
    "    a1[['chr','strand']] = a1[['chr','strand']].astype('category')\n",
    "    counts[organism] = a1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "id": "fe7e0a80-08ef-424f-ad2c-f2fea7edcf3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "organism = 'mouse'\n",
    "segments_of_interest = ['signal','control_down']\n",
    "samples_list = list(samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism]['sample'])\n",
    "condition_list = list(samples_to_analyze_df.loc[samples_to_analyze_df['organism']==organism]['condition'])\n",
    "\n",
    "df = counts[organism]\n",
    "df[samples_list] = df[samples_list].astype('int')\n",
    "\n",
    "df['TSS'] = df.apply(lambda x:x['segment_name'].split(';')[-1]+';'+x['segment_name'].split(';')[1],1)\n",
    "df['segment'] = df.apply(lambda x:x['segment_name'].split(';')[0],1).astype('category')\n",
    "df = df.loc[df['segment'].isin(segments_of_interest)].reset_index(drop=True)\n",
    "\n",
    "df = df[['TSS']+samples_list].groupby(['TSS']).sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "id": "fe036c8d-fc9e-4a70-ae19-df8a6346d13e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rscript /scicore/home/zavolan/mirono0000/Projects/bCLIP/bclip_workflow/scripts/run_deseq2.r /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_in-house/counts.tsv /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_in-house/metadata.tsv si_Ints11 /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_in-house/ fake_gene\n",
      "Rscript /scicore/home/zavolan/mirono0000/Projects/bCLIP/bclip_workflow/scripts/run_deseq2.r /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_public/counts.tsv /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_public/metadata.tsv si_Ints11 /scicore/home/zavolan/GROUP/StefanieCLIP/aleksei/tables/Deseq2/RNAseq_public/ fake_gene\n"
     ]
    }
   ],
   "source": [
    "res_dict = {}\n",
    "for batch in list(samples_to_analyze_df['batch'].unique()):\n",
    "    outdir_path = subdirs['tables_dir']+'Deseq2/RNAseq_'+batch+'/'\n",
    "    count_file_path = subdirs['tables_dir']+'Deseq2/RNAseq_'+batch+'/'+'counts.tsv'\n",
    "    metadata_file_path = subdirs['tables_dir']+'Deseq2/RNAseq_'+batch+'/'+'metadata.tsv'\n",
    "    \n",
    "    out = subprocess.check_output('mkdir -p '+outdir_path, shell=True)\n",
    "    \n",
    "    metadata_df = samples_to_analyze_df.loc[samples_to_analyze_df['batch']==batch].reset_index(drop=True)\n",
    "    counts_df = df[['TSS']+list(metadata_df['sample'])]\n",
    "    metadata_df['sample'] = metadata_df['sample'].str.split('_',expand=True)[0]\n",
    "    counts_df.columns = ['TSS']+list(metadata_df['sample'])\n",
    "    \n",
    "    metadata_df[['sample','condition']].to_csv(metadata_file_path,sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)\n",
    "    counts_df.to_csv(count_file_path,sep=str('\\t'),header=True,index=None,quoting=csv.QUOTE_NONE)\n",
    "    \n",
    "    command = \\\n",
    "    \"\"\"Rscript \"\"\"+subdirs['wf_dir']+'scripts/run_deseq2.r'+' '+count_file_path+' '+metadata_file_path+' si_Ints11 '+outdir_path+' fake_gene'\n",
    "    print(command)\n",
    "    res_dict[batch] = outdir_path+'DE_table.tsv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 443,
   "id": "b586b11c-5261-476b-934a-c1b4de87aedf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "thr_significance = 0.05\n",
    "TSSs_of_interest = {'Junb;85705347':'Junb','Ints11;155954003':'Ints11'}\n",
    "batch = 'public'\n",
    "\n",
    "DE_table = pd.read_csv(res_dict[batch],delimiter=\"\\t\",index_col=None,header=0)\n",
    "DE_table['log2FoldChange'] = DE_table['log2FoldChange'].fillna(0)\n",
    "DE_table[['pvalue','padj']] = DE_table[['pvalue','padj']].fillna(1)\n",
    "DE_table['FDR'] = multipletests(DE_table['pvalue'],method = 'fdr_bh')[1]\n",
    "DE_table['sign'] = (DE_table['pvalue']<thr_significance).astype('int')\n",
    "map_dict = {-1:'pval<'+str(thr_significance)+', $log_2FC<0$',1:'pval<'+str(thr_significance)+', $log_2FC>0$',0:'pval>='+str(thr_significance)}\n",
    "DE_table['RNAseq_cat'] = (DE_table['sign']*((DE_table['log2FoldChange']>0).astype('int')*2-1)).map(map_dict)\n",
    "DE_table['log2_mean'] = np.log2(DE_table['baseMean'])\n",
    "DE_table = DE_table.rename(columns={'gene_name':'TSS'})\n",
    "\n",
    "data = DE_table.copy()\n",
    "data_to_show = data.loc[data['TSS'].isin(TSSs_of_interest)].reset_index(drop=True)\n",
    "\n",
    "x_feature,y_feature,hue = 'log2_mean','log2FoldChange','RNAseq_cat'\n",
    "hue_order = ['pval<'+str(thr_significance)+', $log_2FC>0$','pval>='+str(thr_significance),'pval<'+str(thr_significance)+', $log_2FC<0$']\n",
    "palette = ['pink','grey','orange']\n",
    "\n",
    "sns.set(font_scale=1)\n",
    "sns.set_style(\"white\")\n",
    "fig, axes = plt.subplots(1, 1, sharey=False, sharex=False, figsize=(3,3),)\n",
    "\n",
    "ax = sns.scatterplot(data = data,x=x_feature,y=y_feature,hue=hue,s=3,hue_order = hue_order,palette = palette)\n",
    "ax = sns.scatterplot(data = data_to_show,x=x_feature,y=y_feature,hue=hue,s=20,edgecolor='black',linewidth=1,hue_order = hue_order,palette = palette,\n",
    "                     alpha=1,legend=None)\n",
    "\n",
    "for index, row in data_to_show.iterrows():\n",
    "    if TSSs_of_interest[row['TSS']]=='Junb':\n",
    "        ax.text(row[x_feature]*1.05,row[y_feature],TSSs_of_interest[row['TSS']],ha='left',va='top',size=10)\n",
    "    else:\n",
    "        ax.text(row[x_feature]*0.95,row[y_feature],TSSs_of_interest[row['TSS']],ha='right',va='top',size=10)\n",
    "    \n",
    "ax.set(xlabel = 'average, $log_2$',title='Ints11 siRNA vs mock, RNA-seq')\n",
    "ax.set_ylabel(ylabel=r'$log_2FC$',rotation=0,ha='right',va='center',rotation_mode='anchor')\n",
    "ax.hlines(y=0,xmin=ax.get_xlim()[0],xmax=ax.get_xlim()[1],color='grey',linestyles='--',linewidth=0.7)\n",
    "\n",
    "ax.legend(bbox_to_anchor=(1.001, 0.65),loc=2,borderaxespad=0.0,title='',markerscale=3)\n",
    "\n",
    "out = subprocess.check_output('mkdir -p '+subdirs['figures_dir']+'RNAseq/', shell=True)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/MA_plot.png',bbox_inches='tight',dpi=600)\n",
    "fig.savefig(subdirs['figures_dir']+'RNAseq/MA_plot.pdf',bbox_inches='tight',dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29571ff5-334e-40e5-b428-f5a5faeb1478",
   "metadata": {},
   "outputs": [],
   "source": [
    "### Intersect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "id": "80134a1e-7594-478c-bcf5-d148c1067e31",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TSS</th>\n",
       "      <th>baseMean</th>\n",
       "      <th>log2FoldChange</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>padj</th>\n",
       "      <th>FDR</th>\n",
       "      <th>sign</th>\n",
       "      <th>RNAseq_cat</th>\n",
       "      <th>log2_mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>Jun;94940459</td>\n",
       "      <td>44.898417</td>\n",
       "      <td>1.991924</td>\n",
       "      <td>2.390457e-07</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.000042</td>\n",
       "      <td>1</td>\n",
       "      <td>pval&lt;0.05, $log_2FC&gt;0$</td>\n",
       "      <td>5.488593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1169</th>\n",
       "      <td>Junb;85705347</td>\n",
       "      <td>64.194333</td>\n",
       "      <td>-0.519221</td>\n",
       "      <td>1.304064e-02</td>\n",
       "      <td>0.111358</td>\n",
       "      <td>0.240527</td>\n",
       "      <td>1</td>\n",
       "      <td>pval&lt;0.05, $log_2FC&lt;0$</td>\n",
       "      <td>6.004374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2677</th>\n",
       "      <td>Jund;71151599</td>\n",
       "      <td>189.288310</td>\n",
       "      <td>-0.235770</td>\n",
       "      <td>1.072367e-01</td>\n",
       "      <td>0.399771</td>\n",
       "      <td>0.815808</td>\n",
       "      <td>0</td>\n",
       "      <td>pval&gt;=0.05</td>\n",
       "      <td>7.564442</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                TSS    baseMean  log2FoldChange        pvalue      padj  \\\n",
       "122    Jun;94940459   44.898417        1.991924  2.390457e-07  0.000019   \n",
       "1169  Junb;85705347   64.194333       -0.519221  1.304064e-02  0.111358   \n",
       "2677  Jund;71151599  189.288310       -0.235770  1.072367e-01  0.399771   \n",
       "\n",
       "           FDR  sign              RNAseq_cat  log2_mean  \n",
       "122   0.000042     1  pval<0.05, $log_2FC>0$   5.488593  \n",
       "1169  0.240527     1  pval<0.05, $log_2FC<0$   6.004374  \n",
       "2677  0.815808     0              pval>=0.05   7.564442  "
      ]
     },
     "execution_count": 444,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "data.loc[data['TSS'].str.contains('Jun')]"
   ]
  },
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   "execution_count": null,
   "id": "1805f027-1dcc-4b97-a560-e543bf627ddf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8531bc2e-216d-4991-aacb-63ba3ccad9f2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4eaea0d-9e26-42ee-86a8-87176aca5461",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2e5bee8-2018-42bd-b11a-496b66d9dea6",
   "metadata": {},
   "outputs": [],
   "source": []
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  {
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   "execution_count": null,
   "id": "a96f6710-7100-488b-892d-e08c0b1d2b8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "pivot = pd.pivot_table(df,index=['TSS','chr','strand'],columns='segment',values = samples_list).reset_index()\n",
    "columns = []\n",
    "for elem in pivot.columns:\n",
    "    columns.append(';'.join(elem) if elem[1]!='' else elem[0])\n",
    "pivot.columns = columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "22a2eee0-f0bc-4b96-9180-40f6ec18df3b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
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   "execution_count": null,
   "id": "b202e02f-1833-4b8d-b189-54fe2f25b737",
   "metadata": {},
   "outputs": [],
   "source": []
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  {
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   "execution_count": null,
   "id": "4d0f6b34-1aab-48b0-9115-10e1ab6bff66",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c43ebdb-22ff-4692-b711-7cfde59db113",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de71945b-6e4f-4bf5-93de-4f688c1f9f66",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 464,
   "id": "ef564272-9025-4c55-a5a2-6ccdc2971e44",
   "metadata": {},
   "outputs": [],
   "source": [
    "samples_ints11 = ['Ints11C_replicate5','Ints11C_replicate6']\n",
    "samples_ints10 = ['Ints10N_replicate1','Ints10N_replicate2']\n",
    "samples_back = ['RBC_exp17','RBC_exp18']\n",
    "\n",
    "common_TSS['Ints11'] = ((common_TSS[samples_ints11].sum(axis=1)==2)&(common_TSS[samples_back].sum(axis=1)==0)).astype('int')\n",
    "common_TSS['Ints10'] = ((common_TSS[samples_ints10].sum(axis=1)==2)&(common_TSS[samples_back].sum(axis=1)==0)).astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "id": "1ce2bf01-3ff0-403b-8ede-82da5a194cd3",
   "metadata": {},
   "outputs": [
    {
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       "      <th>gene_name</th>\n",
       "      <th>Ints11C_replicate5</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A1BG</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>1</th>\n",
       "      <td>A1CF</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <th>3</th>\n",
       "      <td>A2ML1</td>\n",
       "      <td>0</td>\n",
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      ],
      "text/plain": [
       "  gene_name  Ints11C_replicate5  Ints11C_replicate6  Ints10N_replicate1  \\\n",
       "0      A1BG                   0                   0                   0   \n",
       "1      A1CF                   0                   0                   0   \n",
       "2       A2M                   0                   0                   0   \n",
       "3     A2ML1                   0                   0                   0   \n",
       "4   A3GALT2                   0                   0                   0   \n",
       "\n",
       "   Ints10N_replicate2  RBC_exp17  RBC_exp18  SRR11551259  SRR11551260  \\\n",
       "0                   0          0          0            0            0   \n",
       "1                   0          0          0            0            0   \n",
       "2                   0          0          0            0            0   \n",
       "3                   0          0          0            0            0   \n",
       "4                   0          0          0            0            0   \n",
       "\n",
       "   SRR11551261  SRR11551262  Ints11  Ints10  \n",
       "0            0            0       0       0  \n",
       "1            0            0       0       0  \n",
       "2            0            0       0       0  \n",
       "3            0            0       0       0  \n",
       "4            0            0       0       0  "
      ]
     },
     "execution_count": 465,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "common_TSS.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d2d6435-bacb-422d-b356-de1f2a4d45a4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 463,
   "id": "c97dce98-1122-41ff-be2c-f5486cdc0142",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <th>72</th>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <th>80</th>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>16170</th>\n",
       "      <td>ZFAND5</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>16173</th>\n",
       "      <td>ZFC3H1</td>\n",
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       "      <td>1</td>\n",
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       "      <th>16183</th>\n",
       "      <td>ZFP36L1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16251</th>\n",
       "      <td>ZMYND8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <th>16279</th>\n",
       "      <td>ZSCAN25</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "<p>667 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      gene_name  Ints11C_replicate5  Ints11C_replicate6  Ints10N_replicate1  \\\n",
       "72       ABHD12                   1                   1                   1   \n",
       "80      ABHD17A                   1                   1                   1   \n",
       "91         ABI1                   1                   1                   1   \n",
       "92         ABI2                   1                   1                   1   \n",
       "97         ABL2                   1                   1                   1   \n",
       "...         ...                 ...                 ...                 ...   \n",
       "16170    ZFAND5                   1                   1                   1   \n",
       "16173    ZFC3H1                   1                   1                   1   \n",
       "16183   ZFP36L1                   1                   1                   1   \n",
       "16251    ZMYND8                   1                   1                   1   \n",
       "16279   ZSCAN25                   1                   1                   1   \n",
       "\n",
       "       Ints10N_replicate2  RBC_exp17  RBC_exp18  SRR11551259  SRR11551260  \\\n",
       "72                      1          0          0            0            0   \n",
       "80                      1          0          0            0            0   \n",
       "91                      1          0          0            0            0   \n",
       "92                      1          0          0            0            0   \n",
       "97                      1          0          0            1            1   \n",
       "...                   ...        ...        ...          ...          ...   \n",
       "16170                   1          0          0            0            0   \n",
       "16173                   0          0          0            0            0   \n",
       "16183                   1          0          0            0            0   \n",
       "16251                   0          0          0            0            0   \n",
       "16279                   1          0          0            0            0   \n",
       "\n",
       "       SRR11551261  SRR11551262  Ints11  \n",
       "72               0            0       1  \n",
       "80               0            0       1  \n",
       "91               0            0       1  \n",
       "92               0            0       1  \n",
       "97               1            1       1  \n",
       "...            ...          ...     ...  \n",
       "16170            0            0       1  \n",
       "16173            0            0       1  \n",
       "16183            0            0       1  \n",
       "16251            0            0       1  \n",
       "16279            0            0       1  \n",
       "\n",
       "[667 rows x 12 columns]"
      ]
     },
     "execution_count": 463,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "common_TSS.loc[common_TSS['Ints11']==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63ad9a95-e248-4330-8323-74c876d73b7b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7f82e1fc-fd3f-4f62-97b3-809d89434bfd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "id": "df770703-f478-41fc-b711-89f611ee140d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TSS</th>\n",
       "      <th>chr</th>\n",
       "      <th>strand</th>\n",
       "      <th>average_log2</th>\n",
       "      <th>lfc</th>\n",
       "      <th>pval</th>\n",
       "      <th>FDR</th>\n",
       "      <th>sign</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21629</th>\n",
       "      <td>Id1;152578171</td>\n",
       "      <td>chr2</td>\n",
       "      <td>+</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.125</td>\n",
       "      <td>1.0</td>\n",
       "      <td>FDR&gt;=0.05</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "                 TSS   chr strand  average_log2  lfc   pval  FDR       sign\n",
       "21629  Id1;152578171  chr2      +           2.0  2.0  0.125  1.0  FDR>=0.05"
      ]
     },
     "execution_count": 283,
     "metadata": {},
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    }
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   "source": [
    "data.loc[data['TSS'].str.contains('')]"
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   "execution_count": 159,
   "id": "d970f980-3b36-4ffb-a150-c58fba3ace8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>TSS</th>\n",
       "      <th>chr</th>\n",
       "      <th>strand</th>\n",
       "      <th>Ints10N_replicate1;control_up</th>\n",
       "      <th>Ints10N_replicate1;signal</th>\n",
       "      <th>Ints10N_replicate2;control_up</th>\n",
       "      <th>Ints10N_replicate2;signal</th>\n",
       "      <th>Ints11C_replicate5;control_up</th>\n",
       "      <th>Ints11C_replicate5;signal</th>\n",
       "      <th>Ints11C_replicate6;control_up</th>\n",
       "      <th>...</th>\n",
       "      <th>Ints10N_replicate1;average_log2</th>\n",
       "      <th>Ints10N_replicate2;pval</th>\n",
       "      <th>Ints10N_replicate2;lfc</th>\n",
       "      <th>Ints10N_replicate2;average_log2</th>\n",
       "      <th>RBC_exp17;pval</th>\n",
       "      <th>RBC_exp17;lfc</th>\n",
       "      <th>RBC_exp17;average_log2</th>\n",
       "      <th>RBC_exp18;pval</th>\n",
       "      <th>RBC_exp18;lfc</th>\n",
       "      <th>RBC_exp18;average_log2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>23017</th>\n",
       "      <td>Jun;94940459</td>\n",
       "      <td>chr4</td>\n",
       "      <td>-</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>4.906891</td>\n",
       "      <td>2.441406e-04</td>\n",
       "      <td>3.700440</td>\n",
       "      <td>3.700440</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23018</th>\n",
       "      <td>Junb;85703171</td>\n",
       "      <td>chr8</td>\n",
       "      <td>-</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>3.459432</td>\n",
       "      <td>5.000000e-01</td>\n",
       "      <td>0.584963</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>23019</th>\n",
       "      <td>Junb;85705347</td>\n",
       "      <td>chr8</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.554589</td>\n",
       "      <td>1.554312e-15</td>\n",
       "      <td>4.781360</td>\n",
       "      <td>5.807355</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23020</th>\n",
       "      <td>Jund;71151599</td>\n",
       "      <td>chr8</td>\n",
       "      <td>+</td>\n",
       "      <td>19</td>\n",
       "      <td>90</td>\n",
       "      <td>21</td>\n",
       "      <td>60</td>\n",
       "      <td>9</td>\n",
       "      <td>44</td>\n",
       "      <td>21</td>\n",
       "      <td>...</td>\n",
       "      <td>6.781360</td>\n",
       "      <td>8.467916e-06</td>\n",
       "      <td>1.471306</td>\n",
       "      <td>6.357552</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 TSS   chr strand  Ints10N_replicate1;control_up  \\\n",
       "23017   Jun;94940459  chr4      -                              0   \n",
       "23018  Junb;85703171  chr8      -                              4   \n",
       "23019  Junb;85705347  chr8      -                              1   \n",
       "23020  Jund;71151599  chr8      +                             19   \n",
       "\n",
       "       Ints10N_replicate1;signal  Ints10N_replicate2;control_up  \\\n",
       "23017                         29                              0   \n",
       "23018                          6                              1   \n",
       "23019                         45                              1   \n",
       "23020                         90                             21   \n",
       "\n",
       "       Ints10N_replicate2;signal  Ints11C_replicate5;control_up  \\\n",
       "23017                         12                              0   \n",
       "23018                          2                              2   \n",
       "23019                         54                              1   \n",
       "23020                         60                              9   \n",
       "\n",
       "       Ints11C_replicate5;signal  Ints11C_replicate6;control_up  ...  \\\n",
       "23017                          4                              0  ...   \n",
       "23018                          1                              5  ...   \n",
       "23019                         19                              0  ...   \n",
       "23020                         44                             21  ...   \n",
       "\n",
       "       Ints10N_replicate1;average_log2  Ints10N_replicate2;pval  \\\n",
       "23017                         4.906891             2.441406e-04   \n",
       "23018                         3.459432             5.000000e-01   \n",
       "23019                         5.554589             1.554312e-15   \n",
       "23020                         6.781360             8.467916e-06   \n",
       "\n",
       "       Ints10N_replicate2;lfc  Ints10N_replicate2;average_log2  \\\n",
       "23017                3.700440                         3.700440   \n",
       "23018                0.584963                         2.000000   \n",
       "23019                4.781360                         5.807355   \n",
       "23020                1.471306                         6.357552   \n",
       "\n",
       "       RBC_exp17;pval  RBC_exp17;lfc  RBC_exp17;average_log2  RBC_exp18;pval  \\\n",
       "23017             1.0            0.0                     0.0             1.0   \n",
       "23018             0.5            1.0                     1.0             1.0   \n",
       "23019             1.0            0.0                     0.0             1.0   \n",
       "23020             1.0            0.0                     0.0             0.5   \n",
       "\n",
       "       RBC_exp18;lfc  RBC_exp18;average_log2  \n",
       "23017            0.0                     0.0  \n",
       "23018           -1.0                     1.0  \n",
       "23019            0.0                     0.0  \n",
       "23020            1.0                     1.0  \n",
       "\n",
       "[4 rows x 33 columns]"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pivot.loc[pivot['TSS'].str.contains('Jun')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc4b6fe9-72a8-4bdd-963b-11297b1462f9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56e8d6f3-2d64-426b-9fec-64cc0d89b482",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c00cb579-5171-431d-a611-b7a35610692c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2b342fcb-48ac-43a8-be07-1a8e320cb1a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# we use not all samples, only good ones\n",
    "experimental_bCLIP_samples = pd.read_csv(subdirs['metadata_dir']+'experimental_bCLIP_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "public_bCLIP_and_ChipSeq_samples = pd.read_csv(subdirs['metadata_dir']+'public_bCLIP_and_ChipSeq_samples.tsv',delimiter=\"\\t\",index_col=None,header=0)\n",
    "\n",
    "samples_to_analyze = ['11C_exp17','11C_exp18','RBC_exp17','RBC_exp18','Ints11C_replicate5','Ints11C_replicate6','Ints10N_replicate1','Ints10N_replicate2',\n",
    "                      'NRDE2_replicate1_exp7','NRDE2_replicate2_exp8','NRDE2_replicate3_exp10','SRR15070630','SRR15070631']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "86077f19-658c-4d44-972f-95a566b667a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>lane_name</th>\n",
       "      <th>lane_file</th>\n",
       "      <th>kmer</th>\n",
       "      <th>barcode_file</th>\n",
       "      <th>exp_ctl</th>\n",
       "      <th>batch</th>\n",
       "      <th>condition_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ints11C_replicate1</td>\n",
       "      <td>2143F1</td>\n",
       "      <td>2143F1-1_190822_D00404_0441_BCDR7LANXX_Undeter...</td>\n",
       "      <td>NNNN</td>\n",
       "      <td>barcodes_2143F1.fasta</td>\n",
       "      <td>exp</td>\n",
       "      <td>old</td>\n",
       "      <td>Ints11C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ints11C_replicate2</td>\n",
       "      <td>2143F1</td>\n",
       "      <td>2143F1-1_190822_D00404_0441_BCDR7LANXX_Undeter...</td>\n",
       "      <td>NNNN</td>\n",
       "      <td>barcodes_2143F1.fasta</td>\n",
       "      <td>exp</td>\n",
       "      <td>old</td>\n",
       "      <td>Ints11C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ints11C_replicate3</td>\n",
       "      <td>2161F1</td>\n",
       "      <td>2161F1-1_190924_D00404_0445_BCDY9VANXX_Undeter...</td>\n",
       "      <td>NNNN</td>\n",
       "      <td>barcodes_2161F1.fasta</td>\n",
       "      <td>exp</td>\n",
       "      <td>old</td>\n",
       "      <td>Ints11C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ints11C_replicate4</td>\n",
       "      <td>2161F1</td>\n",
       "      <td>2161F1-1_190924_D00404_0445_BCDY9VANXX_Undeter...</td>\n",
       "      <td>NNNN</td>\n",
       "      <td>barcodes_2161F1.fasta</td>\n",
       "      <td>exp</td>\n",
       "      <td>old</td>\n",
       "      <td>Ints11C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ints11C_replicate5</td>\n",
       "      <td>2533F1</td>\n",
       "      <td>2533F1-1_200814_D00404_0489_ACECNWANXX_Undeter...</td>\n",
       "      <td>NNNN</td>\n",
       "      <td>barcodes_2533F1.fasta</td>\n",
       "      <td>exp</td>\n",
       "      <td>old</td>\n",
       "      <td>Ints11C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 name lane_name  \\\n",
       "0  Ints11C_replicate1    2143F1   \n",
       "1  Ints11C_replicate2    2143F1   \n",
       "2  Ints11C_replicate3    2161F1   \n",
       "3  Ints11C_replicate4    2161F1   \n",
       "4  Ints11C_replicate5    2533F1   \n",
       "\n",
       "                                           lane_file  kmer  \\\n",
       "0  2143F1-1_190822_D00404_0441_BCDR7LANXX_Undeter...  NNNN   \n",
       "1  2143F1-1_190822_D00404_0441_BCDR7LANXX_Undeter...  NNNN   \n",
       "2  2161F1-1_190924_D00404_0445_BCDY9VANXX_Undeter...  NNNN   \n",
       "3  2161F1-1_190924_D00404_0445_BCDY9VANXX_Undeter...  NNNN   \n",
       "4  2533F1-1_200814_D00404_0489_ACECNWANXX_Undeter...  NNNN   \n",
       "\n",
       "            barcode_file exp_ctl batch condition_name  \n",
       "0  barcodes_2143F1.fasta     exp   old        Ints11C  \n",
       "1  barcodes_2143F1.fasta     exp   old        Ints11C  \n",
       "2  barcodes_2161F1.fasta     exp   old        Ints11C  \n",
       "3  barcodes_2161F1.fasta     exp   old        Ints11C  \n",
       "4  barcodes_2533F1.fasta     exp   old        Ints11C  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experimental_bCLIP_samples.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5cfbe615-89f4-4f5a-9c77-c3a4f7cbf5a4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6297623e-38c7-425b-98d2-7195cdaeeda6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "80eeb107-24da-46f2-8e24-d183a0b9faeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_samples = pd.read_csv(file_paths['input_samples'],delimiter=\"\\t\",index_col=None,header=0)\n",
    "input_samples = input_samples.rename(columns={'name':'sample'})\n",
    "input_samples = input_samples.loc[~input_samples['sample'].isin(samples_to_exclude_from_analysis)].reset_index(drop=True)\n",
    "\n",
    "metadata = input_samples.copy()\n",
    "metadata['group_1'] = metadata.apply(lambda x: x['lane_name'] if x['kmer']=='NNNN' else x['batch'],1)\n",
    "metadata['group_2'] = metadata['exp_ctl'] # group_1 x group_2 are used to block into subplots, and group_3 is on the x axis + color\n",
    "metadata['group_3'] = metadata['condition_name']\n",
    "group_1_order = ['f230802','f230126','f230117','f20220722','f220407','f2533F1','f2161F1','f2143F1','public_bCLIP_mESC','public_eCLIP_Hela']\n",
    "group_2_order = ['exp','neg_ctl','ctl']\n",
    "group_3_order = ['Ints11C','Ints11N','Ints10C','Ints10N','Ints1N','Ints11','NRDE2','Nrde2_D174Rmut','NRDE2_200AANenddel','HP1','RBC','XRN1','N4BP2C','Ccdc174','Eif4a3','Mtrex','Ints11_SMInput','Igg']\n",
    "\n",
    "color_list = ['orange','gold','green','lime','violet','purple','blue','royalblue','cyan','grey','grey','grey','grey','grey','grey','grey','grey','grey']\n",
    "\n",
    "metadata = pd.merge(metadata,pd.DataFrame([group_3_order,color_list]).transpose().rename(columns={0:'group_3',1:'color'}),how='inner',on='group_3')\n",
    "metadata['group_1_x_group_2'] = metadata['group_1']+'-'+metadata['group_2']\n",
    "\n",
    "gr = metadata[['group_1','group_2','group_3']].drop_duplicates().reset_index(drop=True)\n",
    "gr['t']=1\n",
    "gr = gr.groupby(['group_1','group_2']).agg({'t':sum}).reset_index()\n",
    "tmp = gr[['group_1','group_2']].values.tolist()\n",
    "\n",
    "point_plots_width_ratios = []\n",
    "group_1_x_group_2 = []\n",
    "for element in itertools.product(*[group_1_order,group_2_order]):\n",
    "    if list(element) in tmp:\n",
    "        group_1_x_group_2.append(list(element))\n",
    "        point_plots_width_ratios.append(gr.loc[(gr['group_1']==element[0])&(gr['group_2']==element[1])].iloc[0]['t'])\n",
    "        \n",
    "metadata['replicate'] = metadata.apply(lambda x: x['sample'] if x['batch'] not in ['public_bCLIP_mESC','public_eCLIP_Hela'] else x['condition_name']+'_'+x['sample'][-3:],1)"
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