Pedigree Analysis for Quantitative Traits:
Variance Components Without Matrix Inversion
Thompson EA, Shaw RG
Department of Statistics GN22, University of Washington, Seattle.
Biometrics, 46(2):399-413 (1990)
Abstract
Recent developments in the animal breeding literature facilitate estimation of the variance
components in quantitative genetic models. However, computation remains intensive, and
many of the procedures are restricted to specialized designs and models, unsuited to data arising
from studies of natural populations. We develop algorithms that allow maximum likelihood
estimation of variance components for data on arbitrary pedigree structures. The proposed
methods can be implemented on microcomputers, since no intensive matrix computations or
manipulations are involved. Although parts of our procedures have been previously presented,
we unify these into an overall scheme whose intuitive justification clarifies the approach. Two
examples are analyzed: one of data on a natural population of Salivia lyrata and the other of
simulated data on an extended pedigree.
Variance component linkage analysis