- THIS ARTICLE
- Full Text (PDF)
- Alert me when this article is cited
- Alert me if a correction is posted
- SERVICES
- Similar articles in this journal
- Similar articles in PubMed
- Alert me to new issues of the journal
- Download to citation manager
- Reprints & Permissions
- CITING ARTICLES
- Citing Articles via Google Scholar
- GOOGLE SCHOLAR
- Articles by Thompson, E. A.
- Articles by Shaw, R. G.
- Search for Related Content
- PUBMED
- PubMed Citation
- Articles by Thompson, E. A.
- Articles by Shaw, R. G.
Genetics, Vol 131, 971-978, Copyright © 1992
INVESTIGATIONS |
Estimating Polygenic Models for Multivariate Data on Large Pedigrees
E. A. Thompson and R. G. Shaw
Department of Statistics, University of Washington, Seattle, Washington 98115
We have developed algorithms for the likelihood estimation of additive genetic models for quantitative traits on large pedigrees. The approach uses the expectation L-maximization (EM) algorithm, but avoids intensive computation. In this paper, we focus on extensions of previous work to the case of multivariate data. We exemplify the approach by analyses of bivariate data on a four-generation, 949-member pedigree of the snail Lymnaea elodes, and on a three-generation pedigree of the guppy Poecilia reticulata containing about 400 individuals.