Esperanto

Description

An app to analyze Sequencing Data from ONT technology.

This app allows browsing or dragging and dropping FASTQ files. The user may choose a few parameters to filter the data. Then, the program is launched. The workflow in the background is built using Snakemake. The result is a sequence Fasta consensus, with or without the variant calling, along with a statistical report.

Install with Virtualenv (Python Environment)

Requirements

Linux machine (Ubuntu 20.04, Ubuntu 22.04, Fedora)

• Python 3.8 or later
• Virtualenv (for creating a Python virtual environment)
• Dependencies:
  • Ubuntu 20.04 / 22.04 or Fedora:
    • libgtk-3-dev
    • libwebkit2gtk-4.0-dev
    • libffi6 (Ubuntu only)
    • libcanberra-gtk-module
    • dbus-x11
    • build-essential
    • Other development libraries (see the detailed dependencies)

Install Steps

1. Install system dependencies (Ubuntu 20.04 / 22.04):

   sudo add-apt-repository universe
   sudo apt update
   sudo apt install -y libwebkitgtk-1.0-0 libffi6 libgtk-3-dev libreoffice libcanberra-gtk-module dbus-x11

   For Fedora:

   sudo dnf install -y python3-devel freeglut-devel mesa-libGL-devel \
       mesa-libGLU-devel gstreamer1-plugins-base-devel gtk3-devel \
       libjpeg-devel libnotify-devel libpng-devel SDL2-devel libSM-devel \
       libtiff-devel webkit2gtk3-devel libXtst-devel

2. Setup Python Virtual Environment:

   1. Install Python dependencies:

      python3 -m pip install --upgrade pip
      python3 -m pip install virtualenv

   2. Create a new virtual environment:

      python3 -m venv env_wxpython

   3. Activate the virtual environment:

      source env_wxpython/bin/activate

3. Install wxPython: Inside the activated environment, install wxPython:

   pip install wheel
   pip install wxPython PyYAML pandas snakemake pypubsub
   
   

Or run bash setup_virtualenv.sh

Launch GUI on a remote VM

sudo nano /etc/ssh/sshd_config

• set the field X11forwarding to 'yes':

X11Forwarding yes

• save

• Install xauth on ssh server sudo apt update && sudo apt install --assume-yes xauth # Ubuntu and other Debian-based distribution sudo dnf install --assumeyes xorg-x11-xauth # CentOS and other Red Hat based distributions

• Launch SSH connection ssh -X user@IP

• Set in the end of ~/.bashrc export DISPLAY=:0

Running App

cd Esperanto

python u_app.py

User Guide

• Upload one or more of fastq.gz files
• Choose a name for the final repository of the results (default 'WorkingSpace_YYYYMMDD')
• Set min and max length for the step of data filtration
• Set minimum of quantity of reads after the filtration step (Q17-->Q7 progressive to exceed this threshold parameter)
• Set type of sequencing reads
• Set number of threads (minimum 4 is recommended)
• Set Reverse Primer for the orientation of sequences

Go to Results

The results are located inside the workflow/ directory in the directory with the name you specified. (for example workflow/WorkingSpace_YYYYMMDD/)

Main files are :

• All_Consensus_fastas.fasta : Display of consensus sequences after the variant calling, so with degenerated nucleotides.
• All_fastas.fasta : Display of sequences with major nucleotides.
• StatisticReport.tsv : All data from the analysis with fasta sequence.

Understanding each field of StatisticReport:

• QTreshold_1 : Threshold of quality of filtration of reads \
• Depth_1 : Number of reads filtered \
• Identity_Percent_2 : Percentage identity threshold by quality to form the main cluster in order to create a consensus with vsearch \
• Depth_2: Number of reads inside the main cluster in order to create a consensus sequence \
• Mean_read_depth: The average of the depth of the multi-alignment assembling by samtools \
• Breath of coverage: The coverage of the multi-alignment assembling by samtools \
• Length: The length of final consensus \
• Sequence fasta: Sequence consensus (without degenerated nucleotides)