Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan.

Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Research Abstract Details 

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Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Abstract Text:

Iuliana Ionita-Laza,Matthew B McQueen,Nan M Laird,Christoph Lange,Iuliana Ionita-Laza,Matthew B McQueen,Nan M Laird,Christoph Lange,

For genomewide association (GWA) studies in family-based designs, we propose a novel two-stage strategy that weighs the association P values with the use of independently estimated weights. The association information contained in the family sample is partitioned into two orthogonal components--namely, the between-family information and the within-family information. The between-family component is used in the first (i.e., screening) stage to obtain a relative ranking of all the markers. The within-family component is used in the second (i.e., testing) stage in the framework of the standard family-based association test, and the resulting P values are weighted using the estimated marker ranking from the screening step. The approach is appealing, in that it ensures that all the markers are tested in the testing step and, at the same time, also uses information from the screening step. Through simulation studies, we show that testing all the markers is more powerful than testing only the most promising ones from the screening step, which was the method suggested by Van Steen et al. A comparison with a population-based approach shows that the approach achieves comparable power. In the presence of a reasonable level of population stratification, our approach is only slightly affected in terms of power and, since it is a family-based method, is completely robust to spurious effects. An application to a 100K scan in the Framingham Heart Study illustrates the practical advantages of our approach. The proposed method is of general applicability; it extends to any setting in which prior, independent ranking of hypotheses is available.

Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Publishing Authors By Initials

I Ionita-Laza,MB McQueen,NM Laird,C Lange,I Ionita-Laza,MB McQueen,NM Laird,C Lange,

For similar genetic phenomena: inheritance patterns: quantitative trait, heritable research abstracts see: genetic phenomena: inheritance patterns: quantitative trait, heritable research

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Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Journal Published:

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

Journal: American journal of human genetics

VOLUME: 81

Page Numbers: 607-14

Journal Abbreviation: Am. J. Hum. Genet.

ISSN: 0002-9297

DAY: 17

MONTH: 07

YEAR: 2007

Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Information

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LANGUAGE: eng

NlmUniqueID: 370475

Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Keywords Mesh Terms:

KEYWORDS: Quantitative Trait, Heritable

MESH TERMS: genetics

Chemical & Substance for Abstract: Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Information

Substance Name: Genetic Markers

Registry Number: 0

Grant and Affiliation Information for Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan.

AFFILIATION: Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. iionita@hsph.harvard.edu

Country: United States

AGENCY: United States NIMH

GRANT: R01-MH59532

ACRONYM: MH

MEDLINETA: Am J Hum Genet

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