Phantom Epistasis in Genomic Selection: On the Predictive Ability of Epistatic Models.

ABSTRACT: Genomic selection uses whole-genome marker models to predict phenotypes or genetic values for complex traits. Some of these models fit interaction terms between markers, and are therefore called epistatic. The biological interpretation of the corresponding fitted effects is not straightforward and there is the threat of overinterpreting their functional meaning. Here we show that the predictive ability of epistatic models relative to additive models can change with the density of the marker panel. In more detail, we show that for publicly available Arabidopsis and rice datasets, an initial superiority of epistatic models over additive models, which can be observed at a lower marker density, vanishes when the number of markers increases. We relate these observations to earlier results repor

SUBMITTER: Schrauf MF 

PROVIDER: S-EPMC7466977 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature