Testing Genetic Pleiotropy with GWAS Summary Statistics for Marginal and Conditional Analyses.

ABSTRACT: There is growing interest in testing genetic pleiotropy, which is when a single genetic variant influences multiple traits. Several methods have been proposed; however, these methods have some limitations. First, all the proposed methods are based on the use of individual-level genotype and phenotype data; in contrast, for logistical, and other, reasons, summary statistics of univariate SNP-trait associations are typically only available based on meta- or mega-analyzed large genome-wide association study (GWAS) data. Second, existing tests are based on marginal pleiotropy, which cannot distinguish between direct and indirect associations of a single genetic variant with multiple traits due to correlations among the traits. Hence, it is useful to consider conditional analysis, in which a su

SUBMITTER: Deng Y 

PROVIDER: S-EPMC5714448 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature