GitHub - arpcard/rgi: Resistance Gene Identifier (RGI). Software to predict resistomes from protein or nucleotide data, including metagenomics data, based on homology and SNP models. (original) (raw)

The Resistance Gene Identifier (RGI)

This application is used to predict antibiotic resistome(s) from protein or nucleotide data based on homology and SNP models. The application uses reference data from the Comprehensive Antibiotic Resistance Database (CARD).

RGI analyses can be performed via the CARD website RGI portal, via use of a Galaxy wrapper for the Galaxy platform, or alternatively you can install RGI from Conda or run RGI from Docker (see below). The instructions below discuss use of RGI at the command line, following a general overview of how RGI works for genomes, genome assemblies, proteomes, and metagenomic sequencing.

May 2023: Chan Zuckerberg ID (CZ ID) has implemented a web-based platform for RGI analysis of assembled contigs (FASTA) or metagenomic sequencing reads (FASTQ): CZ ID AMR Pipeline Workflow.

CARD reference sequences and significance cut-offs are under constant curation - as CARD curation evolves, the results of RGI evolve.

Overview and Use of RGI

Help Menu and Usage
Loading CARD Reference Databases
Analyzing Genomes, Genome Assemblies, Metagenomic Contigs, or Proteomes (a.k.a. RGI main)
Analyzing Metagenomic Reads (a.k.a. RGI bwt)
K-mer Prediction of Pathogen-of-Origin for AMR Genes (beta-testing)
Running RGI on Digital Alliance (formerly Compute Canada) Serial Farm

License

Use or reproduction of these materials, in whole or in part, by any commercial organization whether or not for non-commercial (including research) or commercial purposes is prohibited, except with written permission of McMaster University. Commercial uses are offered only pursuant to a written license and user fee. To obtain permission and begin the licensing process, see the CARD website.

Citation

Alcock et al. 2023. CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database. Nucleic Acids Research, 51, D690-D699 [PMID 36263822]

Support & Bug Reports

Please log an issue on github issue.

You can email the CARD curators or developers directly at card@mcmaster.ca.

Installation

Recommended installation method for most users is via Conda or Docker. This will handle dependency management and ensure installation of the correct version of RGI's external dependencies e.g., BLAST, DIAMOND.

Install RGI from Conda

Install conda on your system if not already available.

Install mamba from mamba on your system if not already available.

Search for RGI package and show available versions:

mamba search --channel conda-forge --channel bioconda --channel defaults rgi

Create a new Conda environment

mamba create --name rgi --channel conda-forge --channel bioconda --channel defaults rgi

Install RGI package:

mamba install --channel conda-forge --channel bioconda --channel defaults rgi

Install RGI specific version:

mamba install --channel conda-forge --channel bioconda --channel defaults rgi=5.1.1

Remove RGI package:

Install RGI using Docker/Singularity

RGI is available via biocontainers full installed with all databases appropriately loaded.

Install docker on your system if not already available

Pull the Docker container from biocontainers (built from Conda package at https://quay.io/repository/biocontainers/rgi?tab=tags&tag=latest).

docker pull quay.io/biocontainers/rgi:6.0.3--pyha8f3691_0
RGI can be executed from the container as follows:

docker run -v $PWD:/data quay.io/biocontainers/rgi:6.0.3--pyha8f3691_0 rgi -h

Install Development Version

Install Dependencies

The following conda command will install all RGI dependencies (listed below):

git clone https://github.com/arpcard/rgi conda env create -f conda_env.yml conda activate rgi

Install RGI

pip install git+https://github.com/arpcard/rgi.git

python setup.py build python setup.py test python setup.py install