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A multivariate approach to affected‐sib‐pair analysis using highly dense molecular maps
Author(s) -
Bailey Julia N.,
Palmer Christina G.S.,
Woodward J. Arthur,
Smalley Susan L.
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<761::aid-gepi33>3.0.co;2-m
Subject(s) - false positive paradox , multivariate statistics , multivariate analysis , biology , true positive rate , data set , set (abstract data type) , genetics , mathematics , statistics , computational biology , pattern recognition (psychology) , artificial intelligence , computer science , programming language
A multivariate approach to affected‐sib‐pair analyses was performed to localize disease‐susceptibility genes with a minimum number of type I errors (false positives). Using 1,155 independent affected sib pairs extracted from Problem 2A of the GAW10 data set, we were able to localize major genes (MG) 1 and 2. Using 30% of the affected‐sib‐pair sample (N = 337) we were able to localize MG1. False positives were not detected in either of these samples. © 1997 Wiley‐Liss, Inc.