Treatment of Uninformative Families in Mean Allele Sharing Tests for Linkage

Mukhopadhyay Indranil, Feingold Eleanor, Wang Tao, Elston Robert C. and Weeks Daniel E.
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Mukhopadhyay Indranil: Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
Feingold Eleanor: Departments of Human Genetics and Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
Wang Tao: Department of Epidemiology and Biostatistics, Case Western Reserve School of Medicine, Cleveland, OH
Elston Robert C.: Department of Epidemiology and Biostatistics, Case Western Reserve School of Medicine, Cleveland, OH
Weeks Daniel E.: Departments of Human Genetics and Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA

Statistical Applications in Genetics and Molecular Biology, 2006, vol. 5, issue 1, 8

Abstract: Using affected sibling pairs, the mean allele sharing statistic tests for linkage by testing if the mean proportion of alleles that are identical-by-descent (IBD) is equal to a half. The behavior of some versions of the mean allele sharing test statistic depends on whether or not families that are uninformative for their IBD status are included; the SIBPAL version provides less significant values when all families (informative and uninformative) are used than when only informative families are used. Here, we investigate this behavior both analytically and by simulation. Our investigation shows that the main issue is the choice of the variance estimator in the denominator of the statistic. The choice of the denominator is very important and is still not totally resolved. Our mathematical explanation supported by our simulation study might aid in the search for an optimum solution.

Keywords: linkage analysis; mean allele sharing tests; SIBPAL (search for similar items in EconPapers)
Date: 2006
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DOI: 10.2202/1544-6115.1206

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