Integrative analysis of sequencing and array genotype data for discovering disease associations with rare mutations.

ABSTRACT: In the large cohorts that have been used for genome-wide association studies (GWAS), it is prohibitively expensive to sequence all cohort members. A cost-effective strategy is to sequence subjects with extreme values of quantitative traits or those with specific diseases. By imputing the sequencing data from the GWAS data for the cohort members who are not selected for sequencing, one can dramatically increase the number of subjects with information on rare variants. However, ignoring the uncertainties of imputed rare variants in downstream association analysis will inflate the type I error when sequenced subjects are not a random subset of the GWAS subjects. In this article, we provide a valid and efficient approach to combining observed and imputed data on rare variants. We consider comm

SUBMITTER: Hu YJ 

PROVIDER: S-EPMC4313847 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature