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

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...

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Bibliographic Details
Published in:BMC bioinformatics 2014-12, Vol.15 Suppl 17 (Suppl 17), p.S3-S3, Article S3
Main Authors: Chen, Zhongxue, Yang, William, Liu, Qingzhong, Yang, Jack Y, Li, Jing, Yang, Mary
Format: Article
Language:English
Subjects:
Bioinformatics
Biology
Case-Control Studies
Computation
Computer science
Computer Simulation
Conferences
Confidence intervals
Data processing
Genome-Wide Association Study
Genomes
Humans
Hypotheses
Independent study
Information technology
Inverse
Models, Statistical
Probability distribution functions
Public health
Random variables
Statistical methods
Studies
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Summary: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. 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. Simulation study and real data application demonstrate that the proposed method has good performance under some situations.
ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-15-s17-s3