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Improving the power for disease locus detection in affected‐sib‐pair studies by using two‐locus analysis and multiple regression methods
Author(s) -
Cordell Heather J.,
Jacobs Kevin B.,
Wedig Geoffrey C.,
Elston Robert C.
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.1370170784
Subject(s) - locus (genetics) , false positive paradox , genetics , biology , genetic linkage , regression , regression analysis , genome , genome scan , computational biology , statistics , mathematics , gene , allele , microsatellite
In this paper we present a summary of an analysis of the simulated data (Problem 2) for GAW11. We used sib‐pair and affected‐sib‐pair (ASP) methods to evaluate linkage to the mild form of disease at markers across the genome, in data sets of realistic moderate size (containing between 100 and 300 families selected from the simulated replicates). The true ‘answers’ were known in advance. Although in most cases we were successful in detecting linkage to disease in the correct regions, it was often difficult to distinguish these results from false positives elsewhere in the genome. We used two‐locus methods to see whether the significance was improved by simultaneously modeling linkage to two disease loci, and found a modest increase in significance using two‐locus methods in several cases.