Scoary

Scoary performs pan-genome wide association studies by testing associations between accessory genes and phenotypic traits across bacterial genomes.


Key Features:

  • Input Compatibility: Accepts a gene_presence_absence.csv file produced by Roary and a user-created traits file linking genomes to phenotypic traits.
  • Association Analysis: Calculates associations between all accessory genes (genes present in more than one but fewer than all genomes) and specified traits.
  • Sorting by Association Strength: Outputs lists of genes ranked by the strength of their association with each trait.
  • Population Stratification: Accounts for population stratification to reduce confounding from underlying population structure.
  • Minimal Assumptions: Operates with minimal assumptions about evolutionary processes across bacterial species.

Scientific Applications:

  • Pan-genome wide association studies: Identify gene-trait associations within bacterial accessory genomes.
  • Microbial genetics: Map accessory genes linked to specific bacterial phenotypes.
  • Evolutionary biology: Investigate genetic contributions to phenotypic diversity and adaptation in bacterial populations.
  • Applied microbiology: Support studies that relate accessory gene content to phenotypic outcomes in applied microbiology contexts.

Methodology:

Uses Roary's gene_presence_absence.csv and a traits file to test associations between accessory genes (present in >1 and <all genomes) and traits, outputs genes ranked by association strength, and accounts for population stratification while operating with minimal evolutionary assumptions.

Topics

Details

License:
GPL-3.0
Maturity:
Mature
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
Python
Added:
9/12/2016
Last Updated:
6/16/2020

Operations

Data Inputs & Outputs

Publications

Brynildsrud O, Bohlin J, Scheffer L, Eldholm V. Rapid scoring of genes in microbial pan-genome-wide association studies with Scoary. Genome Biology. 2016;17(1). doi:10.1186/s13059-016-1108-8. PMID:27887642. PMCID:PMC5124306.

Documentation

Downloads

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