Genome-Wide Pathway Association Studies of Multiple Correlated Quantitative Phenotypes Using Principle Component Analyses

Open Access

Peer-reviewed

Research Article

Feng Zhang ,

* E-mail: fzhxjtu@gmail.com

Affiliation Key Laboratory of Environment and Gene Related Diseases of Ministry Education, Faculty of Public Health, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
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Xiong Guo,

Affiliation Key Laboratory of Environment and Gene Related Diseases of Ministry Education, Faculty of Public Health, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
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Shixun Wu,

Affiliation Key Laboratory of Environment and Gene Related Diseases of Ministry Education, Faculty of Public Health, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
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Jing Han,

Affiliation Key Laboratory of Environment and Gene Related Diseases of Ministry Education, Faculty of Public Health, College of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China
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Yongjun Liu,

Affiliation Department of Biostatistics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, United States of America
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Hui Shen,

Affiliation Department of Biostatistics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, United States of America
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Hong-Wen Deng

Affiliation Department of Biostatistics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, United States of America
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Genome-wide association studies
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Phenotypes
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Genetics
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Genetics of disease
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Single nucleotide polymorphisms
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Research errors
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Haplotypes
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Principal component analysis
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