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Factors influencing the identification of major genes in a complex disease genome scan
Author(s) -
Yang Huiying,
Wang Yaping,
Goldstein Darlene R.,
Li Zhiming,
Vora Hita,
Cantor Rita 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<933::aid-gepi62>3.0.co;2-m
Subject(s) - linkage (software) , genome scan , genome , identification (biology) , gene , genetics , computational biology , genetic linkage , biology , complex disease , covariate , disease , computer science , medicine , microsatellite , machine learning , allele , botany
A two‐stage linkage strategy was employed to identify major genes for a simulated complex disease via a genome scan. The importance of several approaches for improving the ability to locate major genes has been illustrated. These approaches are: adjusting for covariates, ascertaining through multiple affected family members, increasing the sample size, and using multipoint linkage analysis. © 1997 Wiley‐Liss, Inc.