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. 2013 Jan;37(1):122-9.
doi: 10.1002/gepi.21688. Epub 2012 Oct 2.

Genetic association test for multiple traits at gene level

Xiaobo Guo  1 , Zhifa Liu, Xueqin Wang, Heping Zhang
Affiliations

Genetic association test for multiple traits at gene level

Xiaobo Guo et al. Genet Epidemiol. 2013 Jan.

Abstract

Genome-wide association studies (GWASs) at the gene level are commonly used to understand biological mechanisms underlying complex diseases. In general, one response or outcome is used to present a disease of interest in such studies. In this study, we consider a multiple traits association test from the gene level. We propose and examine a class of test statistics that summarizes the association information between single nucleotide polymorphisms (SNPs) and each of the traits. Our simulation studies demonstrate the advantage of gene-based multiple traits association tests when multiple traits share common genes. Using our proposed tests, we reanalyze the dataset from the Study of Addiction: Genetics and Environment (SAGE). Our result validates previous findings while presenting stronger evidence for consideration of multiple traits.

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Conflict of interest statement

The authors have no conflict of interest.

Figures

Figure 1
Figure 1
The power of the six gene-based association tests at the significance level 0.01 for the simulations with two traits. The solid lines represent the power of the single trait gene-based association test when the Bonferroni adjustment is used. The dash lines represent the power of the multiple trait gene-based tests.
Figure 2
Figure 2
The power of the six gene-based association tests at the significance level of 0.01 for the simulations with three traits. The solid lines represent the power of the single trait gene-based association test when the Bonferroni adjustment is used. The dash lines represent the power of the multiple trait gene-based tests.
See this image and copyright information in PMC

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