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Hi When I use plot(hclust(dist..)...)...) etc to create a dendrogram of a hierarchial cluster analysis, I end up with a vertical tree. What do I need to do to get a horizontal tree? Also, my users are used to seeing trees who's leaves all "end" at the same place (eg. Like in minitab). Is this possible in R? Thanks Mick Michael Watson Head of Informatics Institute for Animal

I'd like to be able to cut dendrograms at a height I specify and then plot the resulting subtrees. I wanted to use the dendrogram object for this purpose because there doesn't seem to be a canned way to cut a hclust object and get a list of hclust objects, but there is a function (cut) that does that for dendrograms. The problem I'm having is that when I plot a dendrogram, I

Hello, It seems that the plot function for dendrograms does not draw labels when they are too long. > hc <- hclust(dist(USArrests), "ave") > dend1 <- as.dendrogram(hc) > dend2 <- cut(dend1, h=70) > dd <- dend2$lower[[1]] > plot(dd) # first label is drawn > attr(dd[[1]], "label") <- "aaaaaaaaaaaaaaaaaa" > plot(dd) # first label is

I am using hclust and plot to produce dendrograms. Using my input data I am able to complete an analysis and obtain a vertical plot. I want to be able to plot the dendrogram horizontally.I am using version 2.6 of R and have updated my packages recently. Using the sample script for dendrograms I can produce a horizontal plot using the instruction horiz = TRUE in plot(). When I use the same

library(mva) data(USArrests) hc <- hclust(dist(USArrests), "ave") plot(hc) # OK dump(c("hc"), "tst") rm(hc) source("tst") plot(hc) # Error in plot.hclust(hc) : invalid dendrogram input The same problem occurs with dput/dget --please do not edit the information below-- Version: platform =

Hi, I use the following clustering methods and get the corresponding dendrograms for single, complete, average, ward and kmeans clustering. This gives the dendrograms, but doesn't show the calculation-way. My question: is there a possibility to show this calculation steps (cluster steps) in matrix or graphical form? Mit freundlichen Gr??en Ralph Modjesch

Hello to all, I still have this doubt. I'd like to colour the different labels of my dendrogram each one with a different colour. How can I do? I guess I could do using *edgetext* and then *t.col* or* lab.col* but I don't know how to add edgetext to my dendrogram. Can you help me please? Example: require(graphics); require(utils) hc <- hclust(dist(USArrests), "ave") (dend1

Dear R-Help, I have a clustering problem with hclust that I hope someone can help me with. Consider the classic hclust example: hc <- hclust(dist(USArrests), "ave") plot(hc) I would like to cut the tree up in such a way so as to avoid small clusters, so that we get a minimum number of items in each cluster, and therefore avoid singletons. e.g. in this example, you can see

Note that cophenetic.default (which works on the output of hclust(dist(X))) uses the row names of X as labels. as.dendrogram.hclust does not retain those row names so cophenetic.dendrogram cannot use them (so it orders them based on the topology of the dendrogram). Bill Dunlap TIBCO Software wdunlap tibco.com On Thu, Apr 21, 2016 at 7:59 AM, William Dunlap <wdunlap at tibco.com> wrote:

Hello, I have been using the "cophenetic" function for objects of class "dendrogram" and I have realised that it gives different results when it is used with objects of class "hclust". For instance, running the first example in the help file of the "cophenetic" function, d1 <- dist(USArrests) hc <- hclust(d1, "ave") d2 <-

Hi, I have a gene expression experiment with 20 samples and 25000 genes each. I'd like to perform clustering on these. It turned out to become much faster when I transform the underlying matrix with t(matrix). Unfortunately then I'm not anymore able to use cutree to access individual clusters. In general I do something like this: hc <- hclust(dist(USArrests), "ave")

Buenas tardes a todos, Estoy interesado en cambiar los límites del eje y en un dendograma construído utilizando la función hclust(). A continuación un ejemplo: hc <- hclust(dist(USArrests), "ave") plot(hc) Hasta aquí todo bien. Si quisiera cambiar los límites del eje "y" de c(0, 200)? Al usar plot(hc, ylim = c(0, 200)) no observo efecto alguno. Qué puedo hacer?

Dear R-users, I would like to change the labels size and format in the node ends of a dendrogram, how can I do it? How can I use different symbols/colors in each node ends ? I manage to do it with plot.cluster, but heat map uses plot.dendrogram. Can anyone help me please? thank you Marta [[alternative HTML version deleted]]

Dear r-list, I am trying to visually seperate the two main clusters of a dendrogram. The idea is to use: 'edgePar=list(lty=3)' for 'dend1[[1]]' and 'edgePar=list(lty=1)' for 'dend1[[2]]' I have not found a way to solve this. Any suggestions? Patrick hc <- hclust(dist(USArrests), "ave") (dend1 <- as.dendrogram(hc)) par(mfrow=c(2,2)) plot(dend1)

Hello to all, I'd like to colour the different labels of my dendrogram. How can I do? I guess I could to using *edgetext* and then* t.col* or *lab.col* but I don't know how to add edgetext to my dendrogram. Can you help me please? Example: require(graphics); require(utils) hc <- hclust(dist(USArrests), "ave") plot(dend1) labels (USArrests) [[1]] # to know how many cities

Hello, I'm having trouble figuring out how to see resulting groups (clusters) from my hclust() output. I have a very large matrix of 4371 plots and 29 species, so simply looking at the graph is impossible. There must be a way to 'print' the results to a table that shows which plots were in what group, correct? I've attached the matrix I'm working with (the whole thing

I am trying to learn how to format Ascii data files for scan or read into R. Precisely for a quickie project, I found some code (at end of this email) to do exactly what I need: To cluster and graph a dendrogram from package (stats). I am stuck on how to format a text file to run the script. I looked at the dataset USArrests (which would be replaced by my data and labels) using UltraEdit. That

Hi, I have the distance matrix computed and I feed it to hclust function. The plot function produces a dense dendrogram as well. But, the cutree function applied does not produce the desired list. Here is the code x=data.frame(similarity_matrix) colnames(x) = c(source_tags_vec) rownames(x) = c(source_tags_vec) clust_tree=hclust(as.dist(x),method="complete") plot(clust_tree)

Dear All, How can the height of a leaf be extracted from a dendrogram? Sure, I can print it, but I am not able to, say, store it in an object. I think I understand that the height is a property of the split, not the leaf itself, but the printing functions display a "height" or "h" (which changes with "hang") and that is what I want. Obviously, the info is there

Hello everyone, Does anyone know how to implement the argument "unit" in R's plclust function ? I used to use Splus where this argument exists but it has not been implemented in R's plclust. The reason why I switched from Splus to R is that Ward's method is not implemented for S's hclust whereas it is implemented for R's hclust. What I would need is S's plclust