Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributions.

ABSTRACT:

Motivation

Genome-wide association studies (GWAS) are an integral tool for studying the architecture of complex genotype and phenotype relationships. Linear mixed models (LMMs) are commonly used to detect associations between genetic markers and a trait of interest, while at the same time allowing to account for population structure and cryptic relatedness. Assumptions of LMMs include a normal distribution of the residuals and that the genetic markers are independent and identically distributed-both assumptions are often violated in real data. Permutation-based methods can help to overcome some of these limitations and provide more realistic thresholds for the discovery of true associations. Still, in practice, they are rarely implemented due to the high computational complexity.

SUBMITTER: John M 

PROVIDER: S-EPMC9486594 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature