Prioritized subset analysis: improving power in genome-wide association studies.

Prioritized subset analysis: improving power in genome-wide association studies. Research Abstract Details 

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Prioritized subset analysis: improving power in genome-wide association studies. Abstract Text:

Chun Li,Mingyao Li,Ethan M Lange,Richard M Watanabe,Chun Li,Mingyao Li,Ethan M Lange,Richard M Watanabe,

BACKGROUND: Genome-wide association studies (GWAS) are now feasible for studying the genetics underlying complex diseases. For many diseases, a list of candidate genes or regions exists and incorporation of such information into data analyses can potentially improve the power to detect disease variants. Traditional approaches for assessing the overall statistical significance of GWAS results ignore such information by inherently treating all markers equally. METHODS: We propose the prioritized subset analysis (PSA), in which a prioritized subset of markers is pre-selected from candidate regions, and the false discovery rate (FDR) procedure is carried out in the prioritized subset and its complementary subset, respectively. RESULTS: The PSA is more powerful than the whole-genome single-step FDR adjustment for a range of alternative models. The degree of power improvement depends on the fraction of associated SNPs in the prioritized subset and their nominal power, with higher fraction of associated SNPs and higher nominal power leading to more power improvement. The power improvement can be substantial; for disease loci not included in the prioritized subset, the power loss is almost negligible. CONCLUSION: The PSA has the flexibility of allowing investigators to combine prior information from a variety of sources, and will be a useful tool for GWAS.

Prioritized subset analysis: improving power in genome-wide association studies. Publishing Authors By Initials

C Li,M Li,EM Lange,RM Watanabe,C Li,M Li,EM Lange,RM Watanabe,

For similar genetic phenomena: variation (genetics): polymorphism, genetic: polymorphism, single nucleotide research abstracts see: genetic phenomena: variation (genetics): polymorphism, genetic: polymorphism, single nucleotide research

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Prioritized subset analysis: improving power in genome-wide association studies. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Human heredity

VOLUME: 65

Page Numbers: 129-41

Journal Abbreviation: Hum. Hered.

ISSN: 1423-0062

DAY: 12

MONTH: 10

YEAR: 2007

Prioritized subset analysis: improving power in genome-wide association studies. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 200525

Prioritized subset analysis: improving power in genome-wide association studies. Keywords Mesh Terms:

KEYWORDS: Polymorphism, Single Nucleotide

MESH TERMS: methods

Chemical & Substance for Abstract: Prioritized subset analysis: improving power in genome-wide association studies. Information

Substance Name: Genetic Markers

Registry Number: 0

Grant and Affiliation Information for Prioritized subset analysis: improving power in genome-wide association studies.

AFFILIATION: Department of Biostatistics, Center for Human Genetics Research, Vanderbilt University School of Medicine, Nashville, TN 37232, USA. chun.li@vanderbilt.edu

Country: Switzerland

AGENCY: United States NIDDK

GRANT: R01 DK066368-03

ACRONYM: DK

MEDLINETA: Hum Hered

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