An assessment of the performance of the logistic mixed model for analyzing binary traits in maize and sorghum diversity panels.

ABSTRACT: The logistic mixed model (LMM) is well-suited for the genome-wide association study (GWAS) of binary agronomic traits because it can include fixed and random effects that account for spurious associations. The recent implementation of a computationally efficient model fitting and testing approach now makes it practical to use the LMM to search for markers associated with such binary traits on a genome-wide scale. Therefore, the purpose of this work was to assess the applicability of the LMM for GWAS in crop diversity panels. We dichotomized three publicly available quantitative traits in a maize diversity panel and two quantitative traits in a sorghum diversity panel, and them performed a GWAS using both the LMM and the unified mixed linear model (MLM) on these dichotomized traits. Our res

SUBMITTER: Shenstone E 

PROVIDER: S-EPMC6248992 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature