Transition-transversion encoding and genetic relationship metric in ReliefF feature selection improves pathway enrichment in GWAS.

ABSTRACT:

Background

ReliefF is a nearest-neighbor based feature selection algorithm that efficiently detects variants that are important due to statistical interactions or epistasis. For categorical predictors, like genotypes, the standard metric used in ReliefF has been a simple (binary) mismatch difference. In this study, we develop new metrics of varying complexity that incorporate allele sharing, adjustment for allele frequency heterogeneity via the genetic relationship matrix (GRM), and physicochemical differences of variants via a new transition/transversion encoding.

Methods

We introduce a new two-dimensional transition/transversion genotype encoding for ReliefF, and we implement three ReliefF attribute metrics: 1.) genotype mismatch (GM), which is the ReliefF standard, 2.) al

SUBMITTER: Arabnejad M 

PROVIDER: S-EPMC6215626 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature