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Bivariate quantitative trait linkage analysis: Pleiotropy versus co‐incident linkages
Author(s) -
Almasy Laura,
Dyer Thomas D.,
Blangero John
Publication year - 1997
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(1997)14:6<953::aid-gepi65>3.0.co;2-k
Subject(s) - pleiotropy , bivariate analysis , linkage (software) , pedigree chart , quantitative trait locus , univariate , trait , genetic linkage , genetics , biology , statistics , multivariate statistics , gene , mathematics , computer science , phenotype , programming language
Power to detect linkage and localization of a major gene were compared in univariate and bivariate variance components linkage analysis of three related quantitative traits in general pedigrees. Although both methods demonstrated adequate power to detect loci of moderate effect, bivariate analysis improved both power and localization for correlated quantitative traits mapping to the same chromosomal region, regardless of whether co‐localization was the result of pleiotropy. Additionally, a test of pleiotropy versus co‐incident linkage was shown to have adequate power and a low error rate. © 1997 Wiley‐Liss, Inc.