Roary

Roary constructs pan-genomes from annotated prokaryotic genome assemblies to identify core and accessory genes across isolates for comparative population analyses.


Key Features:

  • Pan-genome construction: Calculates the pan-genome for prokaryotic populations from input genome annotations.
  • Core and accessory gene identification: Identifies core genes shared among isolates and accessory genes that vary between them.
  • Input format: Processes annotated assemblies in GFF3 format, typically generated using Prokka (Seemann, 2014).
  • Scalability: Designed to handle large datasets comprising hundreds to thousands of isolates.
  • Performance: Demonstrated to construct a pan-genome from 1,000 isolates in approximately 4.5 hours using 13 GB of RAM.
  • Parallelization: Can leverage multiple processors to improve runtime.
  • Implementation: Implemented in Perl.
  • Accuracy and efficiency: Provides high accuracy in gene clustering while maintaining computational efficiency.

Scientific Applications:

  • Comparative genomics: Analysis of gene presence–absence across prokaryotic isolates to define species- or population-level gene repertoires.
  • Core/accessory genome characterization: Determination of conserved core genes and variable accessory genes for functional and evolutionary studies.
  • Population genomics and evolutionary analysis: Investigation of genetic diversity and evolutionary dynamics within prokaryotic populations.

Methodology:

Processes annotated assemblies in GFF3 format (typically from Prokka) to calculate the pan-genome and identify core and accessory genes; implemented in Perl and supports multi-processor execution.

Topics

Details

Tool Type:
command-line tool
Operating Systems:
Linux, Mac
Programming Languages:
Perl
Added:
8/3/2017
Last Updated:
11/24/2024

Operations

Publications

Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S, Holden MT, Fookes M, Falush D, Keane JA, Parkhill J. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics. 2015;31(22):3691-3693. doi:10.1093/bioinformatics/btv421. PMID:26198102. PMCID:PMC4817141.

Documentation

Links