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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....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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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 |
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. |
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