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- Title
Regression-Based Sib Pair Linkage Analysis for Binary Traits.
- Authors
Zeegers, Maurice P.A.; Rice, John P.; Rijsdijk, Frühling V.; Abecasis, Goncalo R.; Sham, Pak C.
- Abstract
The Haseman-Elston (HE) regression method offers a mathematically and computationally simpler alternative to variance-components (VC) models for the linkage analysis of quantitative traits. However, current versions of HE regression and VC models are not optimised for binary traits. Here, we present a modified HE regression and a liability-threshold VC model for binary-traits. The new HE method is based on the regression of a linear combination of the trait squares and the trait cross-product on the proportion of alleles identical by descent (IBD) at the putative locus, for sibling pairs. We have implemented both the new HE regression-based method and have performed analytic and simulation studies to assess its type 1 error rate and power under a range of conditions. These studies showed that the new HE method is well-behaved under the null hypothesis in large samples, is more powerful than both the original and the revisited HE methods, and is approximately equivalent in power to the liability-threshold VC model. Copyright © 2003 S. Karger AG, Basel
- Publication
Human Heredity, 2003, Vol 55, Issue 2/3, p125
- ISSN
0001-5652
- Publication type
Article
- DOI
10.1159/000072317