Two-locus models of disease: Comparison of likelihood and nonparametric linkage methods

Journal Article · Fri Oct 01 04:00:00 EDT 1993 · American Journal of Human Genetics; (United States)

OSTI ID:5030940

Goldin, L R ^[1]; Weeks, D E ^[2]

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1. National Institute of Mental Health, Bethesda, MD (United States)
2. Univ. of Pittsburgh, PA (United States)

The power to detect linkage for likelihood and nonparametric (Haseman-Elston, affected-sib-pair, and affected-pedigree-member) methods is compared for the case of a common, dichotomous trait resulting from the segregation of two loci. Pedigree data for several two-locus epistatic and heterogeneity models have been simulated, with one of the loci linked to a marker locus. Replicate samples of 20 three-generation pedigrees (16 individuals/pedigree) were simulated and then ascertained for having at least 6 affected individuals. The power of linkage detection calculated under the correct two-locus model is only slightly higher than that under a single locus model with reduced penetrance. As expected, the nonparametric linkage methods have somewhat lower power than does the lod-score method, the difference depending on the mode of transmission of the linked locus. Thus, for many pedigree linkage studies, the lod-score method will have the best power. However, this conclusion depends on how many times the lod score will be calculated for a given marker. The Haseman-Elston method would likely be preferable to calculating lod scores under a large number of genetic models (i.e., varying both the mode of transmission and the penetrances), since such an analysis requires an increase in the critical value of the lod criterion. The power of the affected-pedigree-member method is lower than the other methods, which can be shown to be largely due to the fact that marker genotypes for unaffected individuals are not used. 31 refs., 1 fig., 5 tabs.

• OSTI ID: 5030940
• Journal Information: American Journal of Human Genetics; (United States), Journal Name: American Journal of Human Genetics; (United States) Vol. 53:4; ISSN AJHGAG; ISSN 0002-9297
• Country of Publication: United States
• Language: English

Related Subjects

550400* -- Genetics
59 BASIC BIOLOGICAL SCIENCES
99 GENERAL AND MISCELLANEOUS
990200 -- Mathematics & Computers
BIOLOGICAL MARKERS
DISEASES
EQUATIONS
GENETIC MAPPING
MAPPING
MATHEMATICAL MODELS
PREDICTION EQUATIONS
STATISTICAL MODELS