Unknown

Dataset Information

Benchmarking bacterial genome-wide association study methods using simulated genomes and phenotypes.


ABSTRACT: Genome-wide association studies (GWASs) have the potential to reveal the genetics of microbial phenotypes such as antibiotic resistance and virulence. Capitalizing on the growing wealth of bacterial sequence data, microbial GWAS methods aim to identify causal genetic variants while ignoring spurious associations. Bacteria reproduce clonally, leading to strong population structure and genome-wide linkage, making it challenging to separate true 'hits' (i.e. mutations that cause a phenotype) from non-causal linked mutations. GWAS methods attempt to correct for population structure in different ways, but their performance has not yet been systematically and comprehensively evaluated under a range of evolutionary scenarios. Here, we developed a bacterial GWAS simulator (BacGWASim) to generate b

SUBMITTER: Saber MM 

PROVIDER: S-EPMC7200059 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature