KERNEL MACHINE TESTING COUPLED WITH RANK TRUNCATION METHOD FOR GENETIC PATHWAY ANALYSIS

• Activity Number: 76
• Type: Contributed
• Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
• Sponsor: Biometrics Section
• Author(s): Qi Yan*+ and Nianjun Liu
• Companies: University of Alabama at Birmingham and University of Alabama at Birmingham
• Keywords: Pathway analysis ; SKAT ; ARTP ; Simulation study

Abstract

Genetic pathway represents certain biological mechanisms of diseases and pathway analysis considers the biologically pathway-gene-marker hierarchical structure, while traditional genome-wide association studies (GWAS) strategy usually focuses on single marker analysis. Therefore pathway analyses may potentially complement single-marker analysis and provide additional insights for the genetic architecture of complex diseases thus may lead to more biologically meaningful interpretations. Recently, a number of methods for pathway analysis have been proposed to access the significance of a biological pathway from a collection of single nucleotide polymorphisms. In this study, the performance of the sequence kernel association test (SKAT) and the adaptive rank truncated product (ARTP) test were evaluated, individually or jointly for detecting pathway level effects. The genotype data of 2000 subjects from WTCCC Type I Diabetes were used for simulation studies. We compared SKAT, ARTP-ARTP and SKAT-ARTP. The preliminary results show that SKAT-ARTP has the highest power while maintaining correct Type I error rate in most of the scenarios.