Sherlock: detecting gene-disease associations by matching patterns of expression QTL and GWAS.

ABSTRACT: Genetic mapping of complex diseases to date depends on variations inside or close to the genes that perturb their activities. A strong body of evidence suggests that changes in gene expression play a key role in complex diseases and that numerous loci perturb gene expression in trans. The information in trans variants, however, has largely been ignored in the current analysis paradigm. Here we present a statistical framework for genetic mapping by utilizing collective information in both cis and trans variants. We reason that for a disease-associated gene, any genetic variation that perturbs its expression is also likely to influence the disease risk. Thus, the expression quantitative trait loci (eQTL) of the gene, which constitute a unique "genetic signature," should overlap significantly

SUBMITTER: He X 

PROVIDER: S-EPMC3644637 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature