Simultaneous selection of multiple important single nucleotide polymorphisms in familial genome wide association studies data.

ABSTRACT: We propose a resampling-based fast variable selection technique for detecting relevant single nucleotide polymorphisms (SNP) in a multi-marker mixed effect model. Due to computational complexity, current practice primarily involves testing the effect of one SNP at a time, commonly termed as 'single SNP association analysis'. Joint modeling of genetic variants within a gene or pathway may have better power to detect associated genetic variants, especially the ones with weak effects. In this paper, we propose a computationally efficient model selection approach-based on the e-values framework-for single SNP detection in families while utilizing information on multiple SNPs simultaneously. To overcome computational bottleneck of traditional model selection methods, our method trains one singl

SUBMITTER: Majumdar S 

PROVIDER: S-EPMC10213008 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature