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Covariate effects on linkage and association using a general pair method

Covariate effects on linkage and association using a general pair method The “general pair method” (GPM) is a nonparametric, identity‐by‐state (IBS) method of assessing linkage between a chromosomal marker and a binary phenotype. It is applicable to any pedigree structure, and uses marker information from affected as well as unaffected individuals. Results obtained here from nuclear families (Problem 2A) are contrasted with those from extended pedigrees (Problem 2B). Test statistics for chromosomal linkage between each marker and disease status are contrasted with tests for “direct association” which test the hypothesis that a particular allele is associated disease status across all pedigrees. A novel extension of the GPM is presented here for testing whether the strength of linkage (and/or association) depends on the levels of a covariate (i.e., dependency on gender, age, the levels of the “environmental factor,” or the levels of the “quantitative phenotypes” supplied). The GPM is seen to have some power to detect major gene 1 on chromosome 5, and major gene 3 on chromosome 4. The gender interaction effects proved too small to detect. No direct associations are found. © 1997 Wiley‐Liss, Inc. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Genetic Epidemiology Wiley

Covariate effects on linkage and association using a general pair method

Ward, Patrick J.
Genetic Epidemiology , Volume 14 (6) – Jan 1, 1997
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Publisher
Wiley
Copyright
Copyright © 1997 Wiley‐Liss, Inc.
ISSN
0741-0395
eISSN
1098-2272
DOI
10.1002/(SICI)1098-2272(1997)14:6<1059::AID-GEPI83>3.3.CO;2-S
Publisher site
See Article on Publisher Site

Abstract

The “general pair method” (GPM) is a nonparametric, identity‐by‐state (IBS) method of assessing linkage between a chromosomal marker and a binary phenotype. It is applicable to any pedigree structure, and uses marker information from affected as well as unaffected individuals. Results obtained here from nuclear families (Problem 2A) are contrasted with those from extended pedigrees (Problem 2B). Test statistics for chromosomal linkage between each marker and disease status are contrasted with tests for “direct association” which test the hypothesis that a particular allele is associated disease status across all pedigrees. A novel extension of the GPM is presented here for testing whether the strength of linkage (and/or association) depends on the levels of a covariate (i.e., dependency on gender, age, the levels of the “environmental factor,” or the levels of the “quantitative phenotypes” supplied). The GPM is seen to have some power to detect major gene 1 on chromosome 5, and major gene 3 on chromosome 4. The gender interaction effects proved too small to detect. No direct associations are found. © 1997 Wiley‐Liss, Inc.

Journal

Genetic Epidemiology – Wiley

Published: Jan 1, 1997

Keywords: covariate; linkage; nonparametric

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