PhyloMantel | R Documentation |
Performs a matrix correlation with significance given by a phylogenetic Mantel Test. Pairs of rows and columns are permuted with probability proportional to their phylogenetic distance.
PhyloMantel(
tree,
matrix.1,
matrix.2,
...,
permutations = 1000,
ComparisonFunc = function(x, y) cor(x[lower.tri(x)], y[lower.tri(y)]),
k = 1
)
tree |
phylogenetic tree. Tip labels must match names in input matrices |
matrix.1 |
pair-wise comparison/distance matrix |
matrix.2 |
pair-wise comparison/distance matrix |
... |
additional parameters, currently ignored |
permutations |
Number of permutations used in significance calculation |
ComparisonFunc |
comparison function, default is MatrixCor |
k |
determines the influence of the phylogeny. 1 is strong influence, and larger values converge to a traditional mantel test. |
returns a vector with the comparison value and the proportion of times the observed comparison is smaller than the correlations from the permutations.
This method should only be used when there is no option other than representing data as pair-wise. It suffers from low power, and alternatives should be used when available.
Diogo Melo, adapted from Harmon & Glor 2010
Harmon, L. J., & Glor, R. E. (2010). Poor statistical performance of the Mantel test in phylogenetic comparative analyses. Evolution, 64(7), 2173-2178.
Lapointe, F. J., & Garland, Jr, T. (2001). A generalized permutation model for the analysis of cross-species data. Journal of Classification, 18(1), 109-127.
data(dentus)
data(dentus.tree)
tree = dentus.tree
cor.matrices = dlply(dentus, .(species), function(x) cor(x[-5]))
comparisons = MatrixCor(cor.matrices)
sp.means = dlply(dentus, .(species), function(x) colMeans(x[-5]))
mh.dist = MultiMahalanobis(means = sp.means, cov.matrix = PhyloW(dentus.tree, cor.matrices)$'6')
PhyloMantel(dentus.tree, comparisons, mh.dist, k = 10000)
#similar to MantelCor for large k:
## Not run:
PhyloMantel(dentus.tree, comparisons, mh.dist, k = 10000)
MantelCor(comparisons, mh.dist)
## End(Not run)
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