Twin Research

Articles

Theory and Practice in Quantitative Genetics

Daniëlle Posthumaa1 c1, A. Leo Beema2, Eco J. C. de Geusa3, G. Caroline M. van Baala4, Jacob B. von Hjelmborga5, Ivan Iachinea6 and Dorret I. Boomsmaa7

a1 Department of Biological Psychology,Vrije Universiteit Amsterdam,The Netherlands. danielle@psy.vu.nl

a2 Department of Biological Psychology,Vrije Universiteit Amsterdam,The Netherlands.

a3 Department of Biological Psychology,Vrije Universiteit Amsterdam,The Netherlands.

a4 Department of Biological Psychology,Vrije Universiteit Amsterdam,The Netherlands.

a5 Institute of Public Health, Epidemiology, University of Southern Denmark, Denmark.

a6 Department of Statistics, University of Southern Denmark, Denmark.

a7 Department of Biological Psychology,Vrije Universiteit Amsterdam,The Netherlands.

Abstract

With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each, we show how the theoretical biometrical model can be translated into algebraic equations that may be used to generate scripts for statistical genetic software packages, such as Mx, Lisrel, SOLAR, or MERLIN. For using the former program a web-library (available from http://www.psy.vu.nl/mxbib) has been developed of freely available scripts that can be used to conduct all genetic analyses described in this paper.

Correspondence:

c1 Address for correspondence: Daniëlle Posthuma, Vrije Universiteit, Department of Biological Psychology, van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands.

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