An entropy-based approach for testing genetic epistasis underlying complex diseases.

An entropy-based approach for testing genetic epistasis underlying complex diseases. Research Abstract Details 

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An entropy-based approach for testing genetic epistasis underlying complex diseases. Abstract Text:

Guolian Kang,Weihua Yue,Jifeng Zhang,Yuehua Cui,Yijun Zuo,Dai Zhang,

The genetic basis of complex diseases is expected to be highly heterogeneous, with complex interactions among multiple disease loci and environment factors. Due to the multi-dimensional property of interactions among large number of genetic loci, efficient statistical approach has not been well developed to handle the high-order epistatic complexity. In this article, we introduce a new approach for testing genetic epistasis in multiple loci using an entropy-based statistic for a case-only design. The entropy-based statistic asymptotically follows a chi(2) distribution. Computer simulations show that the entropy-based approach has better control of type I error and higher power compared to the standard chi(2) test. Motivated by a schizophrenia data set, we propose a method for measuring and testing the relative entropy of a clinical phenotype, through which one can test the contribution or interaction of multiple disease loci to a clinical phenotype. A sequential forward selection procedure is proposed to construct a genetic interaction network which is illustrated through a tree-based diagram. The network information clearly shows the relative importance of a set of genetic loci on a clinical phenotype. To show the utility of the new entropy-based approach, it is applied to analyze two real data sets, a schizophrenia data set and a published malaria data set. Our approach provides a fast and testable framework for genetic epistasis study in a case-only design.

An entropy-based approach for testing genetic epistasis underlying complex diseases. Publishing Authors By Initials

G Kang,W Yue,J Zhang,Y Cui,Y Zuo,D Zhang,

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An entropy-based approach for testing genetic epistasis underlying complex diseases. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Journal of theoretical biology

VOLUME: 250

Page Numbers: 362-74

Journal Abbreviation: J. Theor. Biol.

ISSN: 0022-5193

DAY: 6

MONTH: 10

YEAR: 2007

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LANGUAGE: eng

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Grant and Affiliation Information for An entropy-based approach for testing genetic epistasis underlying complex diseases.

AFFILIATION: Department of Statistics and Probability, East Lansing, Michigan State University, MI 48824, USA.

Country: Netherlands

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MEDLINETA: J Theor Biol

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