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
More bioinformatics tutorials can be found on my youtube channel: https://www.youtube.com/channel/UCOJM9xzqDc6-43j2x_vXqCQ \ [You can buy me a coffee: https://www.buymeacoffee.com/bioinfocoach] \ Here is a playlist for bacterial genome analysis: https://www.youtube.com/playlist?list=PLe1-kjuYBZ074A06NOuO9rXCTD3ddoOyz
conda config --add channels conda-forge
conda config --add channels bioconda
conda config --add channels defaults
git clone https://github.com/vappiah/bacterial-genomics-tutorial.git
cd bacterial-genomics-tutorial
conda env create -f environment.yaml
mkdir apps
wget https://github.com/broadinstitute/pilon/releases/download/v1.23/pilon-1.23.jar -O apps/pilon.jar
source activate bacterial-genomics-tutorial
or
conda activate bacterial-genomics-tutorial
chmod +x *.{py,sh,pl}
pip install -r pip-requirements.txt
./download_data.sh
./qc_raw_reads.sh
./trim_reads.sh
./qc_trimmed_reads.sh
./assemble.sh
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
./qc_assembly.sh
./reorder_contigs.sh
./mlst.sh
./amr.sh
./annotate.sh
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
./dendogram.sh
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
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
The result interpretation are available on my youtube video tutorial : https://youtu.be/S_sRo_85jhs
Now that you have been able to perform a bacterial comparative genome analysis. Its time to apply your skills on a real world data. Good luck and see you next time
Vincent Appiah, 2020. Bacterial Genomics Tutorial https://github.com/vappiah/bacterial-genomics-tutorial
or
Vincent Appiah,2020. Youtube https://youtu.be/S_sRo_85jhs