rgi
Tags: bacteria assembly antimicrobial-resistance resistome homology sample-scope
Predict antimicrobial resistance from protein or nucleotide data.
This subworkflow uses the Resistance Gene Identifier (RGI) to predict resistomes based on homology and SNP models. It includes analysis of resistance genes, creation of summary visualizations, and aggregation of results across samples.
Take
assembly: Channel<Record>
| Field | Description |
|---|---|
meta | Groovy Record containing sample information |
assembly | Assembled contigs in FASTA format for resistome prediction |
Emit
Published
The sample_outputs and run_outputs emissions are aggregates of output files that will be published in the entry workflow.
sample_outputs
| Output | Description |
|---|---|
tsv | RGI results in tab-separated format |
json | RGI results in JSON format (optional) |
run_outputs
| Output | Description |
|---|---|
csv | Aggregated results in CSV format |
Module Composition
This subworkflow calls the following modules:
- rgi_main - Predict antibiotic resistance from assemblies.
- rgi_heatmap - Create heatmaps of resistance gene presence/absence.
- csvtk_concat - Concatenate multiple CSV or TSV files into a single table.
Used By
This subworkflow is used by the following workflows:
- rgi - Prediction of antibiotic resistance genes using RGI.
Citations
If you use this in your analysis, please cite the following.
-
Bactopia
Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020) -
Resistance Gene Identifier (RGI)
Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M, Edalatmand A, Huynh W, Nguyen A-L V, Cheng AA, Liu S, Min SY, Miroshnichenko A, Tran H-K, Werfalli RE, Nasir JA, Oloni M, Speicher DJ, Florescu A, Singh B, Faltyn M, Hernandez-Koutoucheva A, Sharma AN, Bordeleau E, Pawlowski AC, Zubyk HL, Dooley D, Griffiths E, Maguire F, Winsor GL, Beiko RG, Brinkman FSL, Hsiao WWL, Domselaar GV, McArthur AG CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic acids research 48.D1, D517-D525 (2020)