Enriching the analysis of genomewide association studies with hierarchical modeling.

Enriching the analysis of genomewide association studies with hierarchical modeling. Research Abstract Details 

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Enriching the analysis of genomewide association studies with hierarchical modeling. Abstract Text:

Gary K Chen,John S Witte,

Genomewide association studies (GWAs) initially investigate hundreds of thousands of single-nucleotide polymorphisms (SNPs), and the most promising SNPs are further evaluated with additional subjects, for replication or a joint analysis. Deciding which SNPs merit follow-up is one of the most crucial aspects of these studies. We present here an approach for selecting the most-promising SNPs that incorporates into a hierarchical model both conventional results and other existing information about the SNPs. The model is developed for general use, its potential value is shown by application, and tools are provided for undertaking hierarchical modeling. By quantitatively harnessing all available information in GWAs, hierarchical modeling may more clearly distinguish true causal variants from noise.

Enriching the analysis of genomewide association studies with hierarchical modeling. Publishing Authors By Initials

GK Chen,JS Witte,

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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Enriching the analysis of genomewide association studies with hierarchical modeling. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: American journal of human genetics

VOLUME: 81

Page Numbers: 397-404

Journal Abbreviation: Am. J. Hum. Genet.

ISSN: 0002-9297

DAY: 26

MONTH: 06

YEAR: 2007

Enriching the analysis of genomewide association studies with hierarchical modeling. Information

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LANGUAGE: eng

NlmUniqueID: 370475

Enriching the analysis of genomewide association studies with hierarchical modeling. Keywords Mesh Terms:

KEYWORDS: Polymorphism, Single Nucleotide

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Grant and Affiliation Information for Enriching the analysis of genomewide association studies with hierarchical modeling.

AFFILIATION: Department of Epidemiology and Biostatistics, University of California-San Francisco, San Francisco, CA 94143-0794, USA.

Country: United States

AGENCY: United States NCI

GRANT: R25T CA112355

ACRONYM: CA

MEDLINETA: Am J Hum Genet

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