A comparison of methods to estimate cross-environment genetic correlations

P. A. Astles, A. J. Moore, R. F. Preziosi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

<jats:title>Abstract</jats:title> <jats:p>Advanced techniques for quantitative genetic parameter estimation may not always be necessary to answer broad genetic questions. However, simpler methods are often biased, and the extent of this determines their usefulness. In this study we compare family mean correlations to least squares and restricted error maximum likelihood (REML) variance component approaches to estimating cross-environment genetic correlations. We analysed empirical data from studies where both types of estimates were made, and from studies in our own laboratories. We found that the agreement between estimates was better when full-sib rather than half-sib estimates of cross-environment genetic correlations were used and when mean family size increased. We also note biases in REML estimation that may be especially important when testing to see if correlations differ from 0 or 1. We conclude that correlations calculated from family means can be used to test for the presence of genetic correlations across environments, which is sufficient for some research questions. Variance component approaches should be used when parameter estimation is the objective, or if the goal is anything other than determining broad patterns.</jats:p>
Original languageEnglish
Pages (from-to)114-122
Number of pages0
JournalJournal of Evolutionary Biology
Volume19
Issue number1
DOIs
Publication statusPublished - 1 Jan 2006

Fingerprint

Dive into the research topics of 'A comparison of methods to estimate cross-environment genetic correlations'. Together they form a unique fingerprint.

Cite this