Description Usage Arguments Value Author(s) References See Also Examples
The function orthobasis.phylo
(also nicknamed me.phylo
)
computes Moran's eigenvectors (ME) associated to a tree. If the tree has
'n' tips, (n-1) vectors will be produced. These vectors form an
orthonormal basis: they are centred to mean zero, have unit variance,
and are uncorrelated. Each vector models a different pattern of
phylogenetic autocorrelation. The first vectors are those with maximum
positive autocorrelation, while the last vectors are those with
maximum negative autocorrelation. ME can be used, for instance, as
regressors to remove phylogenetic autocorrelation from data (see
references).
ME can be obtained from a tree, specifying the
phylogenetic proximity to be used. Alternatively, they can be obtained
directly from a matrix of phylogenetic proximities as constructed by
proxTips
.
1 2 3 4 |
x |
A tree of class |
prox |
a matrix of phylogenetic proximities as returned by |
method |
a character string (full or abbreviated without
ambiguity) specifying the method used to compute proximities;
possible values are: |
a |
the exponent used to compute the proximity (see ? |
An object of class orthobasis
. This is a data.frame with
Moran's eigenvectors in column, with special attributes:
- attr(...,"values"): Moran's index for each vector
- attr(...,"weights"): weights of tips; current implementation uses
only uniform weights
Thibaut Jombart tjombart@imperial.ac.uk
Peres-Neto, P. (2006) A unified strategy for estimating and controlling
spatial, temporal and phylogenetic autocorrelation in ecological models
Oecologica Brasiliensis 10: 105-119.
Dray, S.; Legendre, P. \& Peres-Neto, P. (2006) Spatial modelling: a
comprehensive framework for principal coordinate analysis of
neighbours matrices (PCNM) Ecological Modelling 196:
483-493.
Griffith, D. \& Peres-Neto, P. (2006) Spatial modeling in ecology: the
flexibility of eigenfunction spatial analyses Ecology 87:
2603-2613.
- proxTips
which computes phylogenetic proximities
between tips.
- treePart
which can compute an orthobasis based on
the topology of a phylogeny.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | if(require(ape) && require(phylobase)){
## SIMPLE EXAMPLE ##
## make a tree
x <- rtree(50)
## compute Moran's eigenvectors
ME <- me.phylo(x, met="Abouheif")
ME
## plot the 10 first vectors
obj <- phylo4d(x, as.data.frame(ME[,1:10]))
table.phylo4d(obj, cex.sym=.7, cex.lab=.7)
## Not run:
## REMOVING PHYLOGENETIC AUTOCORRELATION IN A MODEL ##
## use example in ungulates dataset
data(ungulates)
tre <- read.tree(text=ungulates$tre)
plot(tre)
## look at two traits
afbw <- log(ungulates$tab[,1])
neonatw <- log((ungulates$tab[,2]+ungulates$tab[,3])/2)
names(afbw) <- tre$tip.label
names(neonatw) <- tre$tip.label
plot(afbw, neonatw) # relationship between traits
lm1 <- lm(neonatw~afbw)
abline(lm1)
lm1
resid1 <- residuals(lm1)
orthogram(resid1, tre) # residuals are autocorrelated
## compute Moran's eigenvectors (ME)
myME <- me.phylo(tre, method="Abou")
lm2 <- lm(neonatw ~ myME[,1] + afbw) # use for ME as covariable
resid2 <- residuals(lm2)
orthogram(resid2, tre) # there is no longer phylogenetic autocorrelation
## see the difference
table.phylo4d(phylo4d(tre, cbind.data.frame(resid1, resid2)))
## End(Not run)
}
|
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