The genetic relationship among traits can be represented using genetic covariance or G-matrix. The evolutionary relationship among G matrices tells us about the potential stability of the response to natural selection and genetic drift, as well as providing clues about the evolution of the genetic and developmental networks that give rise to genetic coupling among traits.
The following software has been written by Patrick Phillips for general use in the analysis of quantitative genetic datasets. Some of the software is also useful for generating and comparing phenotypic covariance matrices.
This software implements the hierarchical comparision of covariance matrices as devised by Bernhard Flury. Primarily intended for normally distributed phenotypic data, but can also be used for genetic data if family means or strain means are utilized.
CPCrand - Randomization Test of the CPC Hierarchy
Provides significance testing of the Flury hierarchy via a randomization test, and therefore does not depend on the assumption of normally distributed data and chi-square significance test. Can be used on both phenotypic and quantitative genetic data. Currently in beta test. Used in Phillips and Arnold (1999, Evolution 53:1506).
Go to beta test directory
H2boot - Bootstrap Estimates and Tests of Quantitative Genetic Data
This program analyses simple quantitative genetic breeding designs (e.g., full-sib and parent-offspring) and uses a bootstrapping approach to estimate errors and perform significance testing. Also allows comparisons of variance-covariance matrices from multiple populations, and sets errors on reconstructions of the pattern of net selection hypothesized to differentiate the populations. Used in Phillips and Arnold (1999, Evolution 53:1506). Currently in beta test.
Go to beta test directory
H2jack - Jackknife Estimates and Tests of Quantitative Genetic Data
Same features as the above program, but using jackknife based error estimates. Currently in beta test. Contact the author for availability.
Correlation Power Calculator
A Mathematica (v3) notebook for implementing power calculations for correlation coefficients as outlined in Phillips (1998) Designing experiments to maximize the power of detecting correlations. Evolution 52:251-255.
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