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Comparison of variance components and sibpair‐based approaches to quantitative trait linkage analysis in unselected samples
Author(s) -
Williams Jeff T.,
Blangero John
Publication year - 1999
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/(sici)1098-2272(1999)16:2<113::aid-gepi1>3.0.co;2-6
Subject(s) - statistics , linkage (software) , quantitative trait locus , trait , variance (accounting) , variance components , type i and type ii errors , mathematics , sample size determination , statistical power , sampling (signal processing) , benchmark (surveying) , biology , genetics , computer science , accounting , filter (signal processing) , gene , business , computer vision , programming language , geodesy , geography
Abstract We compared the statistical performance of sibpair‐based and variance components approaches to multipoint linkage analysis of a quantitative trait in unselected samples. As a benchmark dataset, we used the simulated family data from Genetic Analysis Workshop 10 [Goldin et al., 1997], and each method was used to screen all 200 replications of the GAW10 genome for evidence of linkage to quantitative trait Q1. The sibpair and variance components methods were each applied to datasets comprising single‐sibpairs and complete sibships, and for further comparison we also applied the variance components method to the nuclear family and extended pedigree datasets. For each analysis, the unbiasedness and efficiency of parameter estimation, the power to detect linkage, and the Type I error rate were estimated empirically. Sibpair and variance components methods exhibited comparable performance in terms of the unbiasedness of the estimate of QTL location and the Type I error rate. Within the single‐sibpair and sibship sampling units, the variance components approach gave consistently superior power and efficiency of parameter estimation. Within each method, the statistical performance was improved by the use of the larger and more informative sampling units. Genet. Epidemiol. 16:113–134, 1999. © 1999 Wiley‐Liss, Inc.