Please note that I simply provide this code for POCP calculation and it is not polished in any way. Thus, the user experience might be not great, but the code does the job. Please feel free to report any issues!
As input use one amino acid sequence FASTA file per genome such as provided by
Prokka. Simply annotate all your genomes
with Prokka first and subsequently organize all your FASTA (*.faa) in one folder
(see example data folder in this repository). The script will then calculate all
pairwise alignments between all FASTA files in the provided folder and use this
information for POCP calculation following Qin, Xie et al.
2014. You can also compare all your *.faa
input files only against one other *.faa file to reduce runtime (see below).
You need ruby, awk, grep, and blastp as installed dependencies (ruby, awk
and grep should be already installed on any Linux system). The easiest way
to install blastp is via conda:
conda create -n pocp -c bioconda blast && conda activate pocp If you have blastp installed and in your PATH, simply skip the above step and clone this repository and execute the following test comand:
git clone https://github.com/hoelzer/pocp.git
cd pocp
chmod +x pocp.rb
./pocp.rb example/ example/results/ 2Important: The first given parameter must be the input dir holding the
*.faa FASTA files, the second parameter must be the output path and the
third parameter must be the number of threads used for blastp searches.
The final output (results.csv) should look like this:
If needed, the following parameters used for filtering the blast results can be adjusted directly in the ruby script:
EVALUE = 1e-5
SEQ_IDENTITY = 0.4
ALN_LENGTH = 0.5Per default all pairwise comparisons of all .faa FASTA files located in the input folder are performed.
Please define a single FASTA filename (not path, only the filename), if comparisons should be only performed against the protein sequences in this file:
./pocp.rb example/ example/results/ 2 Cav_10DC88.faa