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

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....

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Detalles Bibliográficos
Autores principales: Chen, Zhongxue, Yang, William, Liu, Qingzhong, Yang, Jack Y, Li, Jing, Yang, Mary Qu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4304193/
https://www.ncbi.nlm.nih.gov/pubmed/25559433
http://dx.doi.org/10.1186/1471-2105-15-S17-S3
Descripción
Sumario: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.