An improved robust association test for GWAS with multiple diseases
Zhongxue Chen,
Hanwen Huang and
Hon Keung Tony Ng
Statistics & Probability Letters, 2014, vol. 91, issue C, 153-161
Abstract:
In a previous study, we proposed a new design and analysis strategy for Genome-wide Association Studies (GWAS) with multiple diseases but no controls. We have proposed to use an overall chi-square test to test for the association between an SNP with any one of the diseases. The overall chi-square test is not sensitive to the underlying model assumption; however, it does not use the information about the trend among the relative risks of the three genotypes. In this study, we propose a new overall test based on the chi-square partition method. The overall p-value of the proposed approach can be estimated by combining independent p-values from the more powerful one-sided tests which incorporate the trend among the relative risks. Simulation study and real data application show that the proposed test is more powerful and robust.
Keywords: Chi-square partition; Genetic model; Robust test; Trend test (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:91:y:2014:i:c:p:153-161
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DOI: 10.1016/j.spl.2014.04.015
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