Improving Power of Genome-Wide Association Studies with Weighted False Discovery Rate Control and Prioritized Subset Analysis

Wan-Yu Lin; Wen-Chung Lee

doi:10.1371/journal.pone.0033716

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Open Access

Peer-reviewed

Research Article

Improving Power of Genome-Wide Association Studies with Weighted False Discovery Rate Control and Prioritized Subset Analysis

Wan-Yu Lin ,

* E-mail: wlin@uab.edu

Affiliations Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
⨯
Wen-Chung Lee

Affiliations Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan, Research Center for Genes, Environment and Human Health, National Taiwan University, Taipei, Taiwan
⨯

Improving Power of Genome-Wide Association Studies with Weighted False Discovery Rate Control and Prioritized Subset Analysis

Wan-Yu Lin,
Wen-Chung Lee

Published: April 9, 2012
https://doi.org/10.1371/journal.pone.0033716

About the Authors

Wan-Yu Lin

* E-mail: wlin@uab.edu

Affiliations Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America

Wen-Chung Lee

Affiliations Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan, Research Center for Genes, Environment and Human Health, National Taiwan University, Taipei, Taiwan

Competing Interests

The authors have declared that no competing interests exist.

Author Contributions

Conceived and designed the experiments: WYL WCL. Performed the experiments: WYL WCL. Analyzed the data: WYL. Wrote the paper: WYL WCL.

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Genome-wide association studies
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Single nucleotide polymorphisms
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Genomics
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Variant genotypes
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Diabetes mellitus
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Genetic loci
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Genetics
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Type 2 diabetes risk
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