Premium
A genome‐wide scan for a simulated data set using two newly developed methods
Author(s) -
Hsu Li,
Aragaki Corinne,
Quiaoit Filemon,
Wang Xiangjing,
Xu Xiubin,
Zhao Lue Ping
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/gepi.13701707101
Subject(s) - linkage disequilibrium , linkage (software) , nonparametric statistics , genome scan , false positive paradox , genetic linkage , data set , computer science , disequilibrium , genome , computational biology , set (abstract data type) , genetics , statistics , mathematics , biology , artificial intelligence , haplotype , gene , medicine , microsatellite , allele , ophthalmology , programming language
A genome‐wide scan of a simulated data set for fictitious disease genes was conducted using both semiparametric and nonparametric methods. The semiparametric model‐based method, which tests for linkage/linkage disequilibrium separately and together, correctly identified all three underlying disease loci along with two false positives through the linkage analysis. However, the nonparametric model‐free method which tests combined linkage/linkage disequilibrium, failed to yield any results due to the lack of linkage disequilibrium information in the data.