Hierarchical Classes Analysis (HICLAS): A novel data reduction method to examine associations between biallelic SNPs and perceptual organization phenotypes in schizophrenia.

ABSTRACT: The power of SNP association studies to detect valid relationships with clinical phenotypes in schizophrenia is largely limited by the number of SNPs selected and non-specificity of phenotypes. To address this, we first assessed performance on two visual perceptual organization tasks designed to avoid many generalized deficit confounds, Kanizsa shape perception and contour integration, in a schizophrenia patient sample. Then, to reduce the total number of candidate SNPs analyzed in association with perceptual organization phenotypes, we employed a two-stage strategy: first a priori SNPs from three candidate genes were selected (GAD1, NRG1 and DTNBP1); then a Hierarchical Classes Analysis (HICLAS) was performed to reduce the total number of SNPs, based on statistically related SNP clusters.

SUBMITTER: Joseph J 

PROVIDER: S-EPMC4559868 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature