MatrixEpistasis: ultrafast, exhaustive epistasis scan for quantitative traits with covariate adjustment.

ABSTRACT: Motivation:For many traits, causal loci uncovered by genetic mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this 'missing heritability' have been proposed. Single nucleotide polymorphism (SNP)-SNP interaction (epistasis), as one of the compelling models, has been widely studied. However, the genome-wide scan of epistasis, especially for quantitative traits, poses huge computational challenges. Moreover, covariate adjustment is largely ignored in epistasis analysis due to the massive extra computational undertaking. Results:In the current study, we found striking differences among epistasis models using both simulation data and real biological data, suggesting that not only can covariate adjustment remove confounding bias,

SUBMITTER: Zhu S 

PROVIDER: S-EPMC6041989 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature