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Group-combined P-values with applications to genetic association studies

文献类型：期刊论文

作者Hu, Xiaonan1,2; Zhang, Wei3; Zhang, Sanguo1,2; Ma, Shuangge4; Li, Qizhai3
刊名BIOINFORMATICS
出版日期2016-09-15
卷号32期号:18页码:2737-2743
ISSN号1367-4803
DOI10.1093/bioinformatics/btw314
英文摘要Motivation: In large-scale genetic association studies with tens of hundreds of single nucleotide polymorphisms (SNPs) genotyped, the traditional statistical framework of logistic regression using maximumlikelihood estimator (MLE) to infer the odds ratios of SNPsmay notwork appropriately. This is because a large number of odds ratios need to be estimated, and theMLEsmay be not stable when some of the SNPs are in high linkage disequilibrium. Under this situation, the P-value combination procedures seemto provide good alternatives as they are constructed on the basis of single-marker analysis. Results: The commonly used P-value combination methods (such as the Fisher's combined test, the truncated product method, the truncated tail strength and the adaptive rank truncated product) may lose power when the significance level varies across SNPs. To tackle this problem, a group combined P-value method (GCP) is proposed, where the P-values are divided into multiple groups and then are combined at the group level. With this strategy, the significance values are integrated at different levels, and the power is improved. Simulation shows that the GCP can effectively control the type I error rates and have additional power over the existing methods-the power increase can be as high as over 50% under some situations. The proposed GCP method is applied to data from the Genetic Analysis Workshop 16. Among all the methods, only the GCP and ARTP can give the significance to identify a genomic region covering gene DSC3 being associated with rheumatoid arthritis, but the GCP provides smaller P-value.
资助项目National Institutes of Health[NO1-AR-2-2263] ; National Institutes of Health[RO1-AR-44422] ; National Arthritis Foundation ; National Science Foundation of China[11371353] ; National Science Foundation of China[61134013] ; Breakthrough Project of Strategic Priority Program of the Chinese Academy of Sciences[XDB13040600]
WOS研究方向Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics
语种英语
WOS记录号WOS:000384651100002
出版者OXFORD UNIV PRESS
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/23660]  
专题系统科学研究所
通讯作者Li, Qizhai
作者单位1.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
4.Yale Univ, Dept Biostat, New Haven, CT USA
推荐引用方式
GB/T 7714		 Hu, Xiaonan,Zhang, Wei,Zhang, Sanguo,et al. Group-combined P-values with applications to genetic association studies[J]. BIOINFORMATICS,2016,32(18):2737-2743.
APA Hu, Xiaonan,Zhang, Wei,Zhang, Sanguo,Ma, Shuangge,&Li, Qizhai.(2016).Group-combined P-values with applications to genetic association studies.BIOINFORMATICS,32(18),2737-2743.
MLA Hu, Xiaonan,et al."Group-combined P-values with applications to genetic association studies".BIOINFORMATICS 32.18(2016):2737-2743.

入库方式： OAI收割

来源：数学与系统科学研究院

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