Prioritizing genetic variants in GWAS with lasso using permutation-assisted tuning.

ABSTRACT:

Motivation

Large scale genome-wide association studies (GWAS) have resulted in the identification of a wide range of genetic variants related to a host of complex traits and disorders. Despite their success, the individual single-nucleotide polymorphism (SNP) analysis approach adopted in most current GWAS can be limited in that it is usually biologically simple to elucidate a comprehensive genetic architecture of phenotypes and statistically underpowered due to heavy multiple-testing correction burden. On the other hand, multiple-SNP analyses (e.g. gene-based or region-based SNP-set analysis) are usually more powerful to examine the joint effects of a set of SNPs on the phenotype of interest. However, current multiple-SNP approaches can only draw an overall conclusion at the SNP-se

SUBMITTER: Yang S 

PROVIDER: S-EPMC7320616 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature