evolqg (version 0.3-4)

DriftTest: Test drift hypothesis

Description

Given a set of covariance matrices and means for terminals, test the hypothesis that observed divergence is larger/smaller than expected by drift alone using a regression of the between-group variances on the within-group eigenvalues.

Usage

DriftTest(means, cov.matrix, show.plot = TRUE)

Value

list of results containing:

regression: the linear regression between the log of the eigenvalues of the ancestral matrix and the log of the between group variance (projected on the eigenvectors of the ancestral matrix)

coefficient_CI_95: confidence intervals for the regression coefficients

log.between_group_variance: log of the between group variance (projected on the ancestral matrix eigenvectors)

log.W_eVals: log of the ancestral matrix eigenvalues

plot: plot of the regression using ggplot2

Arguments

means

list or array of species means being compared. array must have means in the rows.

cov.matrix

ancestral covariance matrix for all populations

show.plot

Logical. If TRUE, plot of eigenvalues of ancestral matrix by between group variance is showed.

Author

Ana Paula Assis, Diogo Melo

References

Marroig, G., and Cheverud, J. M. (2004). Did natural selection or genetic drift produce the cranial diversification of neotropical monkeys? The American Naturalist, 163(3), 417-428. doi:10.1086/381693

Proa, M., O'Higgins, P. and Monteiro, L. R. (2013), Type I error rates for testing genetic drift with phenotypic covariance matrices: A simulation study. Evolution, 67: 185-195. doi: 10.1111/j.1558-5646.2012.01746.x

Examples

#Input can be an array with means in each row or a list of mean vectors
means = array(rnorm(40*10), c(10, 40)) 
cov.matrix = RandomMatrix(40, 1, 1, 10)
DriftTest(means, cov.matrix)