Exploiting excess sharing: A more powerful test of linkage for affected sib pairs than the transmission/disequilibrium test

Authors
Citation
J. Wicks, Exploiting excess sharing: A more powerful test of linkage for affected sib pairs than the transmission/disequilibrium test, AM J HU GEN, 66(6), 2000, pp. 2005-2008
Citations number
4
Categorie Soggetti
Research/Laboratory Medicine & Medical Tecnology","Molecular Biology & Genetics
Journal title
AMERICAN JOURNAL OF HUMAN GENETICS
ISSN journal
00029297 → ACNP
Volume
66
Issue
6
Year of publication
2000
Pages
2005 - 2008
Database
ISI
SICI code
0002-9297(200006)66:6<2005:EESAMP>2.0.ZU;2-#
Abstract
The transmission/disequilibrium test (TDT) is a popular, simple, and powerf ul test of linkage, which can be used to analyze data consisting of transmi ssions to the affected members of families with any kind pedigree structure , including affected sib pairs (ASPs). Although it is based on the preferen tial transmission of a particular marker allele across families, it is not a valid test of association for ASPs. Martin et al. devised a similar stati stic for ASPs, T-sp, which is also based on preferential transmission of a marker allele but which is a valid test of both linkage and association for ASPs. It is, however, less powerful than the TDT as a test of linkage for ASPs. What I show is that the differences between the TDT and T-sp are due to the fact that, although both statistics are based on preferential transm ission of a marker allele, the TDT also exploits excess sharing in identity -by-descent transmissions to ASPs. Furthermore, I show that both of these s tatistics are members of a family of "TDT-like" statistics for ASPs. The st atistics in this family are based on preferential transmission but also, to varying extents, exploit excess sharing. From this family of statistics, w e see that, although the TDT exploits excess sharing to some extent, it is possible to do so to a greater extent-and thus produce a more powerful test of linkage, for ASPs, than is provided by the TDT. Power simulations condu cted under a number of disease models are used to verify that the most powe rful member of this family of TDT-like statistics is more powerful than the TDT for ASPs.