similar to: Colouring hclust() trees

Hi I have a distance matrix which is computed by user defined method. I would like to plot the dendrogram. I would like to use different color and want the leaves laying down bottom. The script like this. I am not familiar with R. I followed the example shown in http://stat.ethz.ch/R-manual/R-devel/library/stats/html/dendrogram.html dist.obj <- as.dist(matrix.distance) hc.obj <-

Hi Sorry to revisit an old problem, I seemed to solve this in 2004, only for it to resurface :-S I am trying to plot a heatmap, and I don't want the columns of my matrix re-ordered. The function doesn't seem to behave as the help would have you believe: a <- matrix(rnorm(100),nr=20) a.d <- dist(a) a.hc <- hclust(a.d) a.de <- as.dendrogram(a.hc) # columns are re-ordered

Hi When I give the command: > heatmap.2(as.matrix(d),Rowv=as.dendrogram(hc.gene),Colv=FALSE,scale="row ",trace="none",col=greenred.colors(79)) The resulting heatmap has re-ordered my columns! This is time-course data, and I don't want my columns re-ordered! Note from the help: Rowv: determines if and how the _row_ dendrogram should be reordered.

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 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")

Hi, I'm trying to save heatmaps as PDFs. However, the PDF version of the heatmaps (Heatmap_CAFvsTNF_run2.pdf) is blurred when compared to its counterpart, which was saved manually by using the software "Grab" (Heatmap_CAFvsTNF_run2.tiff). -----R code-------- sample_output <- "stroma_run2" filename <-

Core developers, I couldn't find any simple way to send a vector of colors to apply to each terminal in plot.dendrogram() or plot.hclust()---I asked R-help about it a few weeks ago and didn't get any response---so I hacked that functionality into the plot.dendrgram code (see below for hacked function plus examples).... Is there any chance this functionality could be added to the

I generated a heatmap in R using the following commands: > mydata <- read.csv(file="Data.csv", header=TRUE, sep=",") > mydata <- mydata[rowSums(mydata[,-1]^2) >0, ] > rownames(mydata)=mydata$Name > mydata <- mydata[,2:253] > mydatamatrix <- data.matrix(mydata) > mydatascale <- t(scale(t(mydatamatrix))) > hr <-

Hi! I am newbee to R and I am facing the problem in plotting the dedrogram with lot of objects. The lines and labels are overlapped very badly, and writing the graphic to postscript and zooming there is not helping either. I tried cut.dendrogram method, but getting the error that it doesn't exist even though I get the man pages for it. I would not find any solution in web as well, and I

I generated a heatmap in R using the following commands: > mydata <- read.csv(file="Data.csv", header=TRUE, sep=",") > mydata <- mydata[rowSums(mydata[,-1]^2) >0, ] > rownames(mydata)=mydata$Name > mydata <- mydata[,2:253] > mydatamatrix <- data.matrix(mydata) > mydatascale <- t(scale(t(mydatamatrix))) > hr <-

I've been trying to get plot.hclust to work with a hclust object I created and have not had much success. It seems that there is some "hidden" characteristic of a hclust object that I can't see. This is most easily seen in the following example, where plot.hclust works on one object, but when this object is "dumped" and then re-read, plot.hclust no longer works. Is

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 =

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

Hi R helpers... I am having troubles because of the discrepancy between the dendrogram plotted from hclust and what is wrote in the hc2Newick file. I've got a matrix C: > hc <- hclust(dist(C)) > plot(hc) with the: > write(hc2Newick(hc),file='test.newick') both things draw completely different "trees"... I have also tried with the raw distance matrix D and

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

I am doing cluster analysis [hclust(Dist, method="average")] on data that potentially contains redundant objects. As expected, the inclusion of redundant objects affects the clustering result, i.e., the data a1, = a2, = a3, b, c, d, e1, = e2 is likely to cluster differently from the same data without the redundancy, i.e., a1, b, c, d, e1. This is apparent when the outcome is visualized

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

Full_Name: Ivan Egorov Version: 1.8.1 OS: MS Windows 2000, SP4 Submission from: (NULL) (194.186.91.129) V<-t(matrix(scan('C:/V3.dat'),3)) d<-dist(V) hc<-hclust(d) rect.hclust(hc,5) Error message is displayed: Read 24 items Error in rect(m[which[n]] + 0.66, par("usr")[3], m[which[n] + 1] + 0.33, : plot.new has not been called yet Here's my data file

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?

Hello, I've been clustering my data using hclust and cutting the resulting tree with cutree. Separately, I visualize the clusterings with heatmap. Is it possible to have the dendrogram on the heatmap reflect the cutree results? That is, instead of having one large dendrogram, it would have 4 or 25 in the example below. Any guidance on if that's possible or not, and what kinds of