A Selection Operator for Summary Association Statistics Reveals Allelic Heterogeneity of Complex Traits.

ABSTRACT: In recent years, as a secondary analysis in genome-wide association studies (GWASs), conditional and joint multiple-SNP analysis (GCTA-COJO) has been successful in allowing the discovery of additional association signals within detected loci. This suggests that many loci mapped in GWASs harbor more than a single causal variant. In order to interpret the underlying mechanism regulating a complex trait of interest in each discovered locus, researchers must assess the magnitude of allelic heterogeneity within the locus. We developed a penalized selection operator for jointly analyzing multiple variants (SOJO) within each mapped locus on the basis of LASSO (least absolute shrinkage and selection operator) regression derived from summary association statistics. We found that, compared to stepwi

SUBMITTER: Ning Z 

PROVIDER: S-EPMC5812891 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature