Skip to Main content Skip to Navigation
Journal articles

Comparative study of statistical methods for detecting association with rare variants in exome-resequencing data

Abstract : Genome-wide association studies for complex traits are based on the common disease/common variant (CDCV) and common disease/rare variant (CDRV) assumptions. Under the CDCV hypothesis, classical genome-wide association studies using single-marker tests are powerful in detecting common susceptibility variants, but under the CDRV hypothesis they are not as powerful. Several methods have been recently proposed to detect association with multiple rare variants collectively in a functional unit such as a gene. In this paper, we compare the relative performance of several of these methods on the Genetic Analysis Workshop 17 data. We evaluate these methods using the unrelated individual and family data sets. Association was tested using 200 replicates for the quantitative trait Q1. Although in these data the power to detect association is often low, our results show that collapsing methods are promising tools. However, we faced the challenge of assessing the proper type I error to validate our power comparisons. We observed that the type I error rate was not well controlled; however, we did not find a general trend specific to each method. Each method can be conservative or nonconservative depending on the studied gene. Our results also suggest that collapsing and the single-locus association approaches may not be affected to the same extent by population stratification. This deserves further investigation.
Complete list of metadatas

https://www.hal.inserm.fr/inserm-00646164
Contributor : Ed. Bmc <>
Submitted on : Tuesday, November 29, 2011 - 1:07:28 PM
Last modification on : Tuesday, February 18, 2020 - 3:32:02 PM
Long-term archiving on: : Monday, December 5, 2016 - 12:26:25 AM

Files

Identifiers

  • HAL Id : inserm-00646164, version 1

Collections

Citation

Mohamad Saad, Aude Pierre, Nora Bohossian, Matthias Macé, Maria Martinez. Comparative study of statistical methods for detecting association with rare variants in exome-resequencing data. BMC Proceedings, BioMed Central, 2011, 5 (Suppl 9), pp.S33. ⟨inserm-00646164⟩

Share

Metrics

Record views

263

Files downloads

462