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Testing for genetic heterogeneity in the genome search meta‐analysis method
Author(s) -
Lewis Cathryn M.,
Levinson Douglas F.
Publication year - 2006
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.20149
Subject(s) - linkage (software) , statistic , pooling , genetic heterogeneity , statistics , statistical hypothesis testing , statistical power , test statistic , computer science , computational biology , genetics , biology , mathematics , gene , artificial intelligence , phenotype
The Genome Search Meta‐Analysis (GSMA) method is widely used to detect linkage by pooling results of previously published genome‐wide linkage studies. The GSMA uses a non‐parametric summed rank statistic in 30 cM bins of the genome. Zintzaras and Ioannidis ([2005] Genet. Epidemiol. 28:123–137) developed a method of testing for heterogeneity of evidence for linkage in the GSMA, with three heterogeneity statistics ( Q , Ha, B ). They implement two testing procedures, restricted versus unrestricted for the summed rank within the bin. We show here that the rank‐unrestricted test provides a conservative test for high heterogeneity and liberal test for low heterogeneity in linked regions. The rank‐restricted test should therefore be used, despite the extensive simulations needed. In a simulation study, we show that the power to detect heterogeneity is low. For 20 studies of affected sib pairs, simulated assuming linkage in all studies to a gene with sibling relative risk of 1.3, the power to detect low heterogeneity using the Q statistic was 14%. With linkage present in 50% of the studies (to a gene with sibling relative risk of 1.4), the Q heterogeneity statistic had power of 29% to detect high heterogeneity. The power to detect linkage using the summed rank was high in both of these situations, at 98% and 79%, respectively. Although testing for heterogeneity in the GSMA is of interest, the currently available method provides little additional information to that provided by the summed rank statistic. Genet. Epidemiol . 2006. © 2006 Wiley‐Liss, Inc.