COMPILE: a GWAS computational pipeline for gene discovery in complex genomes.

ABSTRACT:

Background

Genome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity.

Results

COMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant

SUBMITTER: Hill MJ 

PROVIDER: S-EPMC9250234 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature