Volume 17, Issue S1 pp. S621-S626
II. Problem 2: Analysis of Simulated Family Data for a Complex Disease
Free Access

A genome-wide scan for a simulated data set using two newly developed methods

Dr. Li Hsu

Corresponding Author

Dr. Li Hsu

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington

Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue, N., NW-805, P.O. Box 19024, Seattle, WA 98109.Search for more papers by this author
Corinne Aragaki

Corinne Aragaki

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington

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Filemon Quiaoit

Filemon Quiaoit

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington

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Xiangjing Wang

Xiangjing Wang

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington

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Xiubin Xu

Xiubin Xu

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington

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Lue Ping Zhao

Lue Ping Zhao

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington

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First published: 21 November 2013

Abstract

A genome-wide scan of a simulated data set for fictitious disease genes was conducted using both semiparametric and nonparametric methods. The semiparametric model-based method, which tests for linkage/linkage disequilibrium separately and together, correctly identified all three underlying disease loci along with two false positives through the linkage analysis. However, the nonparametric model-free method which tests combined linkage/linkage disequilibrium, failed to yield any results due to the lack of linkage disequilibrium information in the data.

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