Identification of grouped rare and common variants via penalized logistic regression.

ABSTRACT: In spite of the success of genome-wide association studies in finding many common variants associated with disease, these variants seem to explain only a small proportion of the estimated heritability. Data collection has turned toward exome and whole genome sequencing, but it is well known that single marker methods frequently used for common variants have low power to detect rare variants associated with disease, even with very large sample sizes. In response, a variety of methods have been developed that attempt to cluster rare variants so that they may gather strength from one another under the premise that there may be multiple causal variants within a gene. Most of these methods group variants by gene or proximity, and test one gene or marker window at a time. We propose a penalized

SUBMITTER: Ayers KL 

PROVIDER: S-EPMC3842118 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature