Identification of functional rare variants in genome-wide association studies using stability selection based on random collapsing

Xin Huang,Yixin Fang,Junhui Wang

doi:10.1186/1753-6561-5-s9-s56

Abstract

Genome-wide association studies are a powerful approach used to identify common variants for complex disease. However, the traditional genome-wide association methods may not be optimal when they are applied to rare variants because of the rare variants’ low frequencies and weak signals. To alleviate the difficulty, investigators have proposed many methods that collapse rare variants. In this paper, we propose a novel ranking method, which we call stability selection based on random collapsing, to rank the candidate rare variants. We use the simulated mini-exome data sets of unrelated individuals from Genetic Analysis Workshop 17 for the analysis. The numerical results suggest that the selection based on a random collapsing method is promising for identifying functional rare variants in genome-wide association studies. Further research to examine the error control property of the proposed method is underway.

Highlights

Genome-wide association studies (GWAS) are a powerful approach to identifying common variants associated with complex disease under the common disease/common variant hypothesis
This hypothesis assumes that common variants of small to modest effect are responsible for common diseases [1]
We analyzed the mini-exome data set of unrelated individuals simulated by Genetic Analysis Workshop 17 (GAW17) following the pilot3 study of the 1000 Genomes Project, which consists of 24,487 autosomal SNPs on 3,205 genes [12]

Summary

Introduction

Genome-wide association studies (GWAS) are a powerful approach to identifying common variants associated with complex disease under the common disease/common variant hypothesis. This hypothesis assumes that common variants of small to modest effect are responsible for common diseases [1]. Some studies suggest that rare variants, typically defined as variants with minor allele frequency (MAF) less than 5%, are more likely to be functional variants [3,4]. This leads to the hypothesis that the complex disease is associated with both common and rare variants.

Methods

Results

Conclusion