search for: ultrametr

Dear R-help listers, Is anyone aware of a function that outputs dendrogram ultrametrics? Cheers, Lisa. PS please reply to me personally as well as to the list because the website wasn't letting me subscribe for some reason. thanks... Lisa Holman Research Officer, Vegetation Dynamics Policy & Science Division NSW Department of Environment & Conservation PO Box 1967,...

...ased on DNA sequence distance in Paup* and read it into R, where it became an object of class "phylo". However, I need it to be classified as a "dendrogram" for my purposes (to use it to order the layout of a heatmap). I get an error using as.hclust.phylo because the tree is not ultrametric. Is there no way to convert a non-ultrametric tree of class "phylo" into a "dendrogram"? With thanks for any help that you may be able to offer, Matt -- Matthew Bakker Ph.D. Candidate Department of Plant Pathology University of Minnesota 495 Borlaug Hall 1991 Upper Buford...

...o include either a distance matrix or a phylogenetic tree as a random effect. The troubles I've had are that: 1. Function lmer() in package lme4 only accepts a data frame column as a random factor and not a distance matrix. 2. Function MCMCglmm() in package MCMCglmm only accepts a rooted and ultrametric phylogenetic tree as a pedigree argument while my tree is neither (and for various reasons I cannot construct one or coerce mine to be a rooted, ultrametric tree). Is there any way around it? I'd appreciate mostly a solution to problem 1. Roey -- Dr. Roey Angel Max-Planck-Institute for...

Using Mathematica, I've performed a hierarchical clustering of 3,107 U. S. counties based on 1995-2000 intercounty migration, using an algorithm of my own devising (see http://arxiv.org/abs/0807.1550). I can also generate the associated 3,107 x 3,107 matrix of ultrametric distances. Unfortunately, as far as I have been able to determine, the Mathematica hierarchical clustering package only produces readable dendrograms with twenty-or-so or fewer units. So, I'm wondering whether I can be more successful in looking at my clustering results overall with R (whic...

...o The new function bind.tree() allows to bind two trees together, possibly handling root edges to give internal branches. o The new function drop.tip() removes the tips in a phylogenetic tree, and trims (or not) the corresponding internal branches. o The new function is.ultrametric() tests if a tree is ultrametric. o The function plot.phylo() has more functionalities such as drawing the branches with different colours and/or different widths, showing the node labels, controling the position and font of the labels, rotating the labels, and controli...

...tance matrix or a phylogenetic tree as a random effect. > The troubles I've had are that: > 1. Function lmer() in package lme4 only accepts a data frame column as a > random factor and not a distance matrix. > 2. Function MCMCglmm() in package MCMCglmm only accepts a rooted and > ultrametric phylogenetic tree as a pedigree argument while my tree is > neither (and for various reasons I cannot construct one or coerce mine > to be a rooted, ultrametric tree). > > Is there any way around it? > I'd appreciate mostly a solution to problem 1. > > Roey

...sr/local/include -fpic -g -O2 -c triangMtd.c -o triangMtd.o gcc -std=gnu99 -I/ebio/abt6/jmao/R/R-2.15.0/include -DNDEBUG -I/usr/local/include -fpic -g -O2 -c triangMtds.c -o triangMtds.o gcc -std=gnu99 -I/ebio/abt6/jmao/R/R-2.15.0/include -DNDEBUG -I/usr/local/include -fpic -g -O2 -c ultrametric.c -o ultrametric.o gcc -std=gnu99 -shared -L/usr/local/lib64 -o ape.so BIONJ.o NNI.o SPR.o TBR.o additive.o ape.o bNNI.o bionjs.o bipartition.o delta_plot.o dist_dna.o heap.o mat_expo.o me.o me_balanced.o me_ols.o mvr.o mvrs.o newick.o nj.o njs.o pic.o plot_phylo.o rTrait.o reorder_phylo.o treePo...

Dear all, I'm trying to use phylo.pca function from phytools for the first time. I'm using an ultrametric tree with 167 tips and all branch lengths transformed to 1. I lunched the pPCA like this: pPCA<-phyl.pca(tree,data,method = "lambda") For some reason it takes for ever and never reaches the end of the process. I tried with method="BM" and the process runs normally. Ha...

...ver time (i.e. as in the "Analyzing diversification with diversitree" manual by Rich FitzJohn on page 23). Code I've been working with is below: library(diversitree) #loads library tree<-read.tree("tree")#loads tree tree<-chronopl(tree, lambda=1,CV=TRUE) #converts to ultrametric states<-read.delim("states", header=TRUE)#load states head(states) #match states to tree states<-structure(states$PC, names=states$Species) names(states)<-tree$tip.label #MuSSE diversitree:::argnames.musse(NULL, 3) #number of states lik<-make.musse(tree, states, 3) argname...

I've been comparing variables among objects (taxa) related by known trees, using phylogentically independent contrasts in the ape package, and want to move on to more complex models e.g. by using gls with appropriate correlation terms. My trees contain lots of (hard) polytomies and information about ancestors, which I've been including- creating fully dichotomous trees by using zero branch

...m() are available for the user to manipulate 2) PCMFit: the goal of PCMFit is to provide a generic tool for inference and selection of phylogenetic comparative models (PCMs). Currently, the package implements Gaussian and mixed Gaussian phylogenetic models (MGPM) over all tree types (including non-ultrametric and polytomic trees). The package supports non-existing traits or missing measurements for some of the traits on some of the species. The package supports specifying measurement error associated with each tip of the tree or inferring a measurement error parameter for a group of tips. The Gaussian...

...m() are available for the user to manipulate 2) PCMFit: the goal of PCMFit is to provide a generic tool for inference and selection of phylogenetic comparative models (PCMs). Currently, the package implements Gaussian and mixed Gaussian phylogenetic models (MGPM) over all tree types (including non-ultrametric and polytomic trees). The package supports non-existing traits or missing measurements for some of the traits on some of the species. The package supports specifying measurement error associated with each tip of the tree or inferring a measurement error parameter for a group of tips. The Gaussian...