Multivariate Pattern Analysis of Genotype-Phenotype Relationships in Schizophrenia.

ABSTRACT: Genetic risk variants for schizophrenia have been linked to many related clinical and biological phenotypes with the hopes of delineating how individual variation across thousands of variants corresponds to the clinical and etiologic heterogeneity within schizophrenia. This has primarily been done using risk score profiling, which aggregates effects across all variants into a single predictor. While effective, this method lacks flexibility in certain domains: risk scores cannot capture nonlinear effects and do not employ any variable selection. We used random forest, an algorithm with this flexibility designed to maximize predictive power, to predict 6 cognitive endophenotypes in a combined sample of psychiatric patients and controls (N = 739) using 77 genetic variants strongly associated

SUBMITTER: Zheutlin AB 

PROVIDER: S-EPMC6101611 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature