Comparative-Analysis-of-Bacterial-genomes

Bioinformatics analysis can be challenging especially for new entrants. The purpose of this repo is to provide scripts that one can quickly use to perform comparative analysis of bacterial genomes. The scripts have been designed to automate majority of tasks so that beginners can get their hands dirty without having to struggle to assemble and use the analysis tools

Download and install anaconda(version 3 recommended)

Add channels

conda config --add channels conda-forge
conda config --add channels bioconda
conda config --add channels defaults

Download the Analysis pipeline

git clone https://github.com/vappiah/bacterial-genomics-tutorial.git

Change directory to the dowloaded folder

cd bacterial-genomics-tutorial

Create conda environment.Packages are listed in the environment.yaml file.

conda env create -f environment.yaml

Download the polishing tool pilon

mkdir apps
wget https://github.com/broadinstitute/pilon/releases/download/v1.23/pilon-1.23.jar -O apps/pilon.jar

Activate the analysis environment

source activate bacterial-genomics-tutorial

or

conda activate bacterial-genomics-tutorial

Add permission to all scripts

chmod +x *.{py,sh,pl}

Install python packages using pip

pip install -r pip-requirements.txt

TIME FOR ANALYSIS

Step 1: Download data.

./download_data.sh

Step 2: Perform QC on the raw reads

./qc_raw_reads.sh

Step 3: Trim reads using sickle

./trim_reads.sh

Step 4: Perform QC on the trimmed reads

./qc_trimmed_reads.sh

Step 5: Perform de novo assembly using spades

./assemble.sh

Step 6 : Polish the draft assembly using pilon

This is meant to improve the draft assembly. The scaffolds will be used. You can also modify the script to use the contigs and compare the result

./polish.sh

Step 7: Perform QC for both raw assembly and polished assembly

./qc_assembly.sh

Step 8: Generate draft genome by reordering contigs against a reference genome using ragtag\

./reorder_contigs.sh

Step 9: Perform a multi locus sequence typing using MLST software\

./mlst.sh

Step 10: Check for antimicrobial resistance genes using abricate\

./amr.sh

Step 11: Annotate the draft genome using prokka

./annotate.sh

Step 12: Get some statistics on the annotation.

Features such as genes, CDS will be counted and displayed. The scripts requires you to specify the folder where annotations were saved . i.e. P7741 Python should be used to run that script

python get_annot_stats.py P7741_annotation P7741

Step 13: Generate dendogram using dREP\

./dendogram.sh

Step 14: Perform Pangenome Analysis using Roary.

Input files are gff (version 3 ) format. It is recommended to use prokka generated gff. So we generate the gffs for the files in the genome folder by reannotating with prokka. We use the get_genome_gffs script
./get_genome_gffs.sh

Then perform pangenome analysis\

./get_pangenome.sh

Step 15: Get gene summary for three of the organism. the default is P7741 Agy99 and Liflandii. A venn diagram will be generated(gene_count_summary.png)

python gene_count_summary.py P7741 Agy99 Liflandii pangenome/gene_presence_absence.csv

If you are working on a cluster you will want to combine the analysis results into a zip file for download and view locally. ./zip_results.sh

Step 16: Compare our draft genome with the other organisms in the genomes folder by generating circular structures for them .

Step 17: Result interpretation

Now that we have been able to perform a bacterial comparative genome analysis. we can apply these skills on other dataset too.