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A new statistical approach to combining p-values using gamma distribution and its application to genome-wide association study

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2014

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BioMed Central
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Chen, Zhongxue, William Yang, Qingzhong Liu, Jack Y Yang, Jing Li, and Mary Qu Yang. 2014. “A new statistical approach to combining p-values using gamma distribution and its application to genome-wide association study.” BMC Bioinformatics 15 (Suppl 17): S3. doi:10.1186/1471-2105-15-S17-S3. http://dx.doi.org/10.1186/1471-2105-15-S17-S3.

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Abstract

Background: Combining information from different studies is an important and useful practice in bioinformatics, including genome-wide association study, rare variant data analysis and other set-based analyses. Many statistical methods have been proposed to combine p-values from independent studies. However, it is known that there is no uniformly most powerful test under all conditions; therefore, finding a powerful test in specific situation is important and desirable. Results: In this paper, we propose a new statistical approach to combining p-values based on gamma distribution, which uses the inverse of the p-value as the shape parameter in the gamma distribution. Conclusions: Simulation study and real data application demonstrate that the proposed method has good performance under some situations.

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Fisher test, Lancaster method, rare variant association test, z-test

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