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GATE: an efficient procedure in study of pleiotropic genetic associations
Zhang, Wei1,2; Yang, Liu3; Tang, Larry L.4,7; Liu, Aiyi5; Mills, James L.5; Sun, Yuanchang6; Li, Qizhai1
Source PublicationBMC GENOMICS
AbstractBackground: The association studies on human complex traits are admittedly propitious to identify deleterious genetic markers. Compared to single-trait analyses, multiple-trait analyses can arguably make better use of the information on both traits and markers, and thus improve statistical power of association tests prominently. Principal component analysis (PCA) is a well-known useful tool in multivariate analysis and can be applied to this task. Generally, PCA is first performed on all traits and then a certain number of top principal components (PCs) that explain most of the trait variations are selected to construct the test statistics. However, under some situations, only utilizing these top PCs would lead to a loss of important evidences from discarded PCs and thus makes the capability compromised. Methods: To overcome this drawback while keeping the advantages of using the top PCs, we propose a group accumulated test evidence (GATE) procedure. By dividing the PCs which is sorted in the descending order according to the corresponding eigenvalues into a few groups, GATE integrates the information of traits at the group level. Results: Simulation studies demonstrate the superiority of the proposed approach over several existing methods in terms of statistical power. Sometimes, the increase of power can reach 25%. These methods are further illustrated using the Heterogeneous Stock Mice data which is collected from a quantitative genome-wide association study. Conclusions: Overall, GATE provides a powerful test for pleiotropic genetic associations.
KeywordPleiotropic genetic associations Principal component analysis Power Biomedical study
Funding ProjectSpecial National Key Research and Development Plan[2016YFD0400206] ; Strategic Priority Program of the Chinese Academy of Sciences[XDB13040600] ; National Science Foundation of China[11371353]
WOS Research AreaBiotechnology & Applied Microbiology ; Genetics & Heredity
WOS SubjectBiotechnology & Applied Microbiology ; Genetics & Heredity
WOS IDWOS:000406619400001
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Document Type期刊论文
Corresponding AuthorLi, Qizhai
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing, Peoples R China
2.Yale Univ, Sch Publ Hlth, Dept Biostat, New Haven, CT USA
3.China Univ Min & Technol, Coll Geosci & Surveying Engn, Beijing, Peoples R China
4.George Mason Univ, Dept Stat, Fairfax, VA 22030 USA
5.NICHHD, Div Intramural Populat Hlth Res, Eunice Kennedy Shriver, NIH, Bethesda, MD 20892 USA
6.Florida Int Univ, Dept Math & Stat, Miami, FL 33199 USA
7.NIH, Dept Rehabil Med, Ctr Clin, Bldg 10, Bethesda, MD 20892 USA
Recommended Citation
GB/T 7714
Zhang, Wei,Yang, Liu,Tang, Larry L.,et al. GATE: an efficient procedure in study of pleiotropic genetic associations[J]. BMC GENOMICS,2017,18:15.
APA Zhang, Wei.,Yang, Liu.,Tang, Larry L..,Liu, Aiyi.,Mills, James L..,...&Li, Qizhai.(2017).GATE: an efficient procedure in study of pleiotropic genetic associations.BMC GENOMICS,18,15.
MLA Zhang, Wei,et al."GATE: an efficient procedure in study of pleiotropic genetic associations".BMC GENOMICS 18(2017):15.
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