Premium
Comparison of model‐free linkage mapping strategies for the study of a complex trait
Author(s) -
Amos C.I.,
Krushkal J.,
Thiel T.J.,
Young A.,
Zhu D.K.,
Boerwinkle E.,
de Andrade M.
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<743::aid-gepi30>3.0.co;2-o
Subject(s) - linkage (software) , quantitative trait locus , trait , locus (genetics) , statistics , variance (accounting) , genetic linkage , biology , chromosome , statistical power , analysis of variance , genetics , variance components , computational biology , mathematics , computer science , gene , accounting , business , programming language
Abstract We compared several strategies for identifying and estimating effects from a genetic locus in the etiology of a complex trait. For our analyses we used data from simulated trait 1 and chromosome 5. Results from analysis of the first 20 replicates showed that a components of variance test provided considerably better power for identifying linkage than tests that consider pair differences. We also compared the power from constructing tests with a single marker, an approximate method using five markers jointly, or a multipoint analysis using all 25 markers on chromosome 5 jointly. Results from this analysis showed substantially better power when all markers were jointly used in the analysis. Results from considering all replicates showed that all methods of estimation provided maximal test statistics at the correct marker position, but the components of variance procedure provided more power to detect the correct position than other methods. © 1997 Wiley‐Liss, Inc.