👩‍⚕Dr. PRG - Drug resistance Prediction with Reference Graphs️👨‍⚕️

codecov Rust github release version License: MIT 10.1099/mgen.0.001081

Full documentation: https://mbh.sh/drprg/

As the name suggests, Dr. PRG (pronounced "Doctor P-R-G") is a tool for predicting drug resistance from sequencing data. It can be used for any species, provided an index is available for that species. The documentation outlines which species have prebuilt indices and also a guide for how to create your own.

Quick Installation

conda install -c bioconda drprg

Linux is currently the only supported platform; however, there is a Docker container that can be used on other platforms.

See the installation guide for more options.

Quick usage

Download the latest M. tuberculosis prebuilt index

drprg index --download mtb

Predict resistance from an Illumina fastq

drprg predict -x mtb -i reads.fq --illumina -o outdir/

Help

$ drprg -h
Drug Resistance Prediction with Reference Graphs

Usage: drprg [OPTIONS] <COMMAND>

Commands:
  build    Build an index to predict resistance from
  predict  Predict drug resistance
  index    Download and interact with indices
  help     Print this message or the help of the given subcommand(s)

Options:
  -v, --verbose        Use verbose output
  -t, --threads <INT>  Maximum number of threads to use [default: 1]
  -h, --help           Print help (see more with '--help')
  -V, --version        Print version

Citation

Hall MB, Lima L, Coin LJM, Iqbal Z (2023) Drug resistance prediction for Mycobacterium tuberculosis with reference graphs. Microbial Genomics 9:001081. doi: 10.1099/mgen.0.001081

@article{hall_drug_2023,
	title = {Drug resistance prediction for {Mycobacterium} tuberculosis with reference graphs},
	volume = {9},
	copyright = {All rights reserved},
	issn = {2057-5858},
	url = {https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.001081},
	doi = {10.1099/mgen.0.001081},
	number = {8},
	journal = {Microbial Genomics},
	author = {Hall, Michael B. and Lima, Leandro and Coin, Lachlan J. M. and Iqbal, Zamin},
	year = {2023},
	pages = {001081},
}