EPAV is a pan-genome analysis pipeline using presence-absence variations(PAVs) of small genomic elements inside or in flanking regions of genes instead of the whole genes. It is capable to capture more genotype-phenotype associations in the map-to-pan alignments than traditional gene PAV analysis pipeline. Altering PAV unit from gene to more detailed functional segments or elements might lead to more biological insights.
EPAV takes map-to-pan alignments and BED format element coordinates as standard input. It computes coverage of each element and reports element PAVs in PAV table and VCF format. Then it serves as a toolbox for further element PAVs analysis including PCA and element PAV-GWAS.
Requirements
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Python 3.6 or later (https://www.python.org/)
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Python package
Python package pandas is needed. Follow the Installation step, or you can install the package by yourself.
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R 3.6 or later (https://www.r-project.org/)
R is utilized for visualization and statistical tests in EPAV toolbox. Please install R first and make sure R and Rscript are under your PATH.
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R packages
R packages ggplot2, ggrepel and Com 66C0 plexHeatmap are needed. Follow the Installation step, or you can install the packages by yourself.
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Supporting software
Supporting software Samtools, PLINK and EMMAX are needed. Follow the Installation step, or you can install the software by yourself.
Installation procedures
## install EPAV
git clone --recursive https://github.com/SJTU-CGM/EPAV
## install supporting tools
cd ${EPAV_PATH}/tools && bash install_tools.sh
pip3 install pandas
Rscript ${EPAV_PATH}/tools/install_r_packages.R
Usage
python3 ${EPAV_PATH}/epav.py [command] [options]
## Available commands:
gfftobed Convert gff to bed format based on chosen element.
getdp Get mapping depth of each base in each chosen gene element.
dptocov Compute coverage of each gene element.
covtopav Determine presence or absence of each gene element.
pavgwas Apply PAV-GWAS.
plot Visualize EPAV result.
## get help
python3 ${EPAV_PATH}/epav.py --help
python3 ${EPAV_PATH}/epav.py [command] --help
Demo
Follow the instructions below to run the demo.
cd ${EPAV_PATH}/demo
# 1.Download example data
bash download_example_data.sh
# 2.Run demo
bash run_demo.sh