Reprioritizing genetic associations in hit regions using LASSO-based resample model averaging.

ABSTRACT: Significance testing one SNP at a time has proven useful for identifying genomic regions that harbor variants affecting human disease. But after an initial genome scan has identified a "hit region" of association, single-locus approaches can falter. Local linkage disequilibrium (LD) can make both the number of underlying true signals and their identities ambiguous. Simultaneous modeling of multiple loci should help. However, it is typically applied ad hoc: conditioning on the top SNPs, with limited exploration of the model space and no assessment of how sensitive model choice was to sampling variability. Formal alternatives exist but are seldom used. Bayesian variable selection is coherent but requires specifying a full joint model, including priors on parameters and the model space. Penal

SUBMITTER: Valdar W 

PROVIDER: S-EPMC3470705 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature