Generalized Structured Component Analysis in candidate gene association studies: applications and limitations.

ABSTRACT: Background: Generalized Structured Component Analysis (GSCA) is a component-based alternative to traditional covariance-based structural equation modelling. This method has previously been applied to test for association between candidate genes and clinical phenotypes, contrasting with traditional genetic association analyses that adopt univariate testing of many individual single nucleotide polymorphisms (SNPs) with correction for multiple testing. Methods: We first evaluate the ability of the GSCA method to replicate two previous findings from a genetics association study of developmental language disorders. We then present the results of a simulation study to test the validity of the GSCA method under more restrictive data conditions, using smaller sample sizes and larger

SUBMITTER: Thompson PA 

PROVIDER: S-EPMC7818107 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature