amppred

Snakemake pipeline to perform consensus antimicrobial prediction on a set of proteins in fasta format using three tools based on machine learning.

Usage

Put the target files in the directory samples as a fasta file with the extension ".faa" and run: snakemake --use-conda -j <cores>

Requirements

• Conda
• Snakemake
• Ampep
• AmpGram
• AMP scanner v2
• Python packages: pandas, seaborn and scipy.

Model references

• Burdukiewicz, M. et al. Proteomic Screening for Prediction and Design of Antimicrobial Peptides with AmpGram. Int J Mol Sci 21, 4310 (2020).
• Lawrence, T. J. et al. amPEPpy 1.0: A portable and accurate antimicrobial peptide prediction tool. Bioinformatics btaa917- (2020) doi:10.1093/bioinformatics/btaa917.
• Daniel Veltri, Uday Kamath, Amarda Shehu, Deep learning improves antimicrobial peptide recognition, Bioinformatics, Volume 34, Issue 16, 15 August 2018, Pages 2740–2747, https://doi.org/10.1093/bioinformatics/bty179