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Open AccessJournal ArticleDOI

The comparison of quantitative genetic parameters between populations

Ruth G. Shaw
- 01 Feb 1991 - 
- Vol. 45, Iss: 1, pp 143-151
TLDR
A statistical method for comparing matrices of genetic variation and covariation between groups (e.g., species, populations, a single population grown in distinct environments) and provides a framework for isolating the particular components that differ significantly between the groups.
Abstract
A statistical method for comparing matrices of genetic variation and covariation between groups (e.g., species, populations, a single population grown in distinct environments) is proposed. This maximum-likelihood method provides a test of the overall null hypothesis that two covariance component matrices are identical. Moreover, when the overall null hypothesis is rejected, the method provides a framework for isolating the particular components that differ significantly between the groups. Simulation studies reveal that discouragingly large experiments are necessary to obtain acceptable power for comparing genetic covariance component matrices. For example, even in cases of a single trait measured on 900 individuals in a nested design of 100 sires and three dams per sire in each population, the power was only about 0.5 when additive genetic variance differed by a factor of 2.5. Nevertheless, this flexible method makes valid comparison of covariance component matrices possible.

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Citations
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Journal Article

Human biochemical genetics

Grüneberg H
- 01 Jul 1960 - 
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
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Adaptive phenotypic plasticity: consensus and controversy.

TL;DR: Current issues are laid out and the areas of consensus and controversy surrounding the evolution of plasticity and the reaction norm (the set of phenotypes produced by a genotype over a range of environments) are summarized.
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Constraints on phenotypic evolution.

TL;DR: A unifying framework that considers all four major varieties of constraint is emerging within the discipline of quantitative genetics, and this work attempts to sketch that emerging framework and summarize recent efforts toward unification.
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Comparative quantitative genetics : evolution of the G matrix

TL;DR: It is proposed that a new field, comparative quantitative genetics, has emerged and the strengths and weaknesses of the many statistical and conceptual approaches now being employed are compared.
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A comparison of phenotypic variation and covariation patterns and the role of phylogeny, ecology, and ontogeny during cranial evolution of new world monkeys

TL;DR: P phenotypic co‐variance and correlation structure is compared among Platyrrhine Neotropical primates to help evaluate the evolution of relationships among traits in response to new functional and developmental relationships.
References
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Book

Introduction to quantitative genetics

TL;DR: The genetic constitution of a population: Hardy-Weinberg equilibrium and changes in gene frequency: migration mutation, changes of variance, and heritability are studied.
Journal ArticleDOI

Analyzing tables of statistical tests

TL;DR: Technique non parametrique pour la signification statistique de tables de tests utilisees dans les etudes sur l'evolution notamment.
Journal Article

Human biochemical genetics

Grüneberg H
- 01 Jul 1960 - 
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Book

Multivariate statistical methods

TL;DR: In this article, a text designed to make multivariate techniques available to behavioural, social, biological and medical students is presented, which includes an approach to multivariate inference based on the union-intersection and generalized likelihood ratio principles.
Journal ArticleDOI

Recovery of inter-block information when block sizes are unequal

TL;DR: In this article, a modified maximum likelihood procedure is proposed for estimating intra-block and inter-block weights in the analysis of incomplete block designs with block sizes not necessarily equal, and the method consists of maximizing the likelihood, not of all the data, but of selected error contrasts.