Original Paper

Testing for Linkage underRobust Genetic Models
R. Guerra^a, Y. Wan^c, A. Jia^a, C.I. Amos^d, J.C. Cohen<sup>b

a</sup>Biostatistics Center, Department of Statistical Science, Southern Methodist University and
^bCenter for Human Nutrition, University of Texas Southwestern Medical Center, Dallas, Tex.;
^cDepartment of Internal Medicine, University of Texas Houston Medical School, University Clinical Research Center and
^dDepartment of Epidemiology, University of Texas, M.D. Anderson Cancer Center, Houston, Tex., USA

Address of Corresponding Author

Hum Hered 1999;49:146-153 (DOI: 10.1159/000022863)

  Key Words

• Linkage
• Significance test
• Monte Carlo
• Variance components

  Abstract

Robust genetic models are used to assess linkage between a quantitative trait and genetic variation at a specific locus using allele-sharing data. Little is known about the relative performance of different possible significance tests under these models. Under the robust variance components model approach there are several alternatives: standard Wald and likelihood ratio tests, a quasilikelihood Wald test, and a Monte Carlo test. This paper reports on the relative performance (significance level and power) of the robust sibling pair test and the different alternatives under the robust variance components model. Simulations show that (1) for a fixed sample size of nuclear families, the variance components model approach is more powerful than the robust sibling pair approach; (2) when the number of nuclear families is at least ~100 and heritability at the trait locus is moderate to high (>0.20) all tests based on the variance components model are equally effective; (3) when the number of nuclear families is less than ~100 or heritability at the trait locus is low (<0.20), on balance, the Monte Carlo test provides the best power and is the most valid. The different testing procedures are applied to determine which are able to detect the known association between low density lipoprotein cholesterol and the common genotypes at the locus encoding apolipoprotein E. Results from this application show that the robust sibling pair method may be more effective in practice than that indicated by simulations.

  Author Contacts

Rudy Guerra
Department of Statistical Science, Southern Methodist University
144 Heroy Hall, 3225 Daniel Avenue
Dallas, TX 75275-0332 (USA)
Tel. +1 214 768 2270, Fax +1 214 768 4035, E-Mail rguerra@mail.smu.edu

  Article Information

Received: Received: July 20, 1998
Revision received: December 9, 1998
Accepted: December 18, 1998
Number of Print Pages : 8
Number of Figures : 4, Number of Tables : 5, Number of References : 38