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

BMC Bioinformatics

Research

Jack Y Yang¹  William Yang²  Qingzhong Liu³  Zhongxue Chen⁴  Jing Li⁴  Mary Qu Yang⁵ 

[1] Center for Compuational Biology and Bioinformatics, Indiana University School of Medicine, 46202, Indianaplois, Indiana, USA;Division of Biostatistics and Biomathematics, Massachusetts General Hospital and Harvard Medicial School, 02114, Boston, Massachusetts, USA;Department of Computer Science, George W. Donaghey College of Engineering and Information Technology, University of Arkansas at Little Rock, 2801 S. University Avenue, 72204, Little Rock, Arkansas, USA;Department of Computer Science, Sam Houston State University, 77341, Huntsville, Texas, USA;Department of Epidemiology and Biostatistics, Indiana University School of Public Health, 1025 E. 7th street, PH C104, 47405, Bloomington, Indiana, USA;MidSouth Bioinformatics Center, Department of Information Science, George W. Donaghey College of Engineering and Information Technology, University of Arkansas at Little Rock, 2801 S. University Avenue, 72204, Little Rock, Arkansas, USA;Joint Bioinformatics Graduate Program, University of Arkansas at Little Rock and University of Arkansas for Medical Sciences, 72204, Little Rock, Arkansas, USA;

关键词: Fisher test;    Lancaster method;    rare variant association test;    z-test;   

DOI  :  10.1186/1471-2105-15-S17-S3

来源: Springer

【 摘 要 】

BackgroundCombining 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.ResultsIn 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.ConclusionsSimulation study and real data application demonstrate that the proposed method has good performance under some situations.

【 授权许可】

CC BY   
© Chen et al.; licensee BioMed Central Ltd. 2014