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

Xiaonan Hu | Zendy; Wei Zhang | Zendy; Sanguo Zhang | Zendy; Shuangge Ma | Zendy; Qizhai Li | Zendy

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

Author(s) -

Xiaonan Hu,

Wei Zhang,

Sanguo Zhang,

Shuangge Ma,

Qizhai Li

Publication year - 2016

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btw314

Subject(s) - linkage disequilibrium , statistics , single nucleotide polymorphism , estimator , genetic association , mathematics , computer science , biology , genetics , genotype , gene

In large-scale genetic association studies with tens of hundreds of single nucleotide polymorphisms (SNPs) genotyped, the traditional statistical framework of logistic regression using maximum likelihood estimator (MLE) to infer the odds ratios of SNPs may not work appropriately. This is because a large number of odds ratios need to be estimated, and the MLEs may be not stable when some of the SNPs are in high linkage disequilibrium. Under this situation, the P-value combination procedures seem to provide good alternatives as they are constructed on the basis of single-marker analysis.

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