similar to: Is there a way to print branch distances for hclust function?

I have used heatmap to visualize my microarray data. I have a matrix of M-values. I do the following. #The distance between the columns. sampdist <- dist(t(matrix[,]), method="euclidean") sclus <- hclust(sampdist, method="average") #The distance between the rows. genedist <- dist(matrix[,], method="euclidean") gclus <- hclust(genedist,

I am using R for hierarchical clustering of a number of documents. I have a distance matrix on which I have applied hclust method. When I plot the result of hclust method, I can see the dendogram plotted. What I need now is the dendogram stored as a tree in a data structure. My goal is to automatically label all internal nodes. For that, I need to know, which leaf nodes make a first level

I have a data which contain some NA value in their elements. What I want to do is to **perform clustering without removing rows** where the NA is present. I understand that `gower` distance measure in `daisy` allow such situation. But why my code below doesn't work? __BEGIN__ # plot heat map with dendogram together. library("gplots") library("cluster")

I am trying to make dendogram based on gene expression matrix , but getting some error: I countMatrix = read.table("count.row.txt",header=T,sep='\t',check.names=F) colnames(countMatrix) count_matrix <- countMatrix[,-1] # remove first column (gene names) rownames(count_matrix) <- countMatrix[,1] #added first column gene names as rownames) >

Hi,   I need to generate a heatmap on a square matrix and wouldn't want to reorder the columns and the rows on the heatmap display.    I have used the options Rowv=NULL and Colv=NULL but doesn't seem to work. Following is a snippet of the heatmap function i am using. args <- commandArgs(); inputfile <- args[2] imgfile   <- args[3] bitmap(imgfile, height=15, width=15, res=100,

Hi everybody! Anybody knows how can I get detalied information about clusters after using hclust? The issue is that if I have some items in different clusters, I would like to get the cluster where each item is placed. Taking into account that my data set is too large, it is not useful to have the dendogram or a graphic, and really I need something like a simple table with item label and cluster

Hello, I would like to cut a hclust tree into several groups at a specific similarity. I assume this can be achieved by specifying the "h" argument with the specified similarity, e.g.: clust<-hclust(dist,"average") cut<-cutree(clust,h=0.65) Now, I would like to draw rectangles around the branches of the dendrogram highlighting the corresponding clusters, as is done by

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)

I've found that while cutree() and rect.hclust() make the same classes for a given height in the dendrogram, the actual labeling of the classes is different. For example, both produce the same 4 classes but class 1 according to cutree() is class 4 according to rect.hclust(). Would it be possible that future versions provide the same labeling? rect.hclust() is useful to display the classes

Hello everyone! I have two questions regarding cluster analysis with the package 'cluster' : 1. I have a dissimilarity matrix in csv format, and I would like to use it to generate a dendogram using 'hclust'. How do I make that matrix compatible with the function? I think it has to be similar to the objects generated by the 'dist' function. Any ideas? 2. Does

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

Basic question: Is it correct to assume that when using cutree to set the # clusters (say k=4), cutree determines the clusters by the largest distances among all potential clusters? I've read the R help for cutree and am using it to define the number of groups to obtain Dunn Index scores (using clValid library) for cluster analysis (using Euclidean Distance and Ward's method) More

Hi Rafael, What about multivariate logistic regression? ----- Forwarded Message ---- From: Rafael Duarte <rduarte@ipimar.pt> To: Anders Malmendal <anders@chem.au.dk> Cc: r-help@stat.math.ethz.ch Sent: Tuesday, May 29, 2007 3:21:11 PM Subject: Re: [R] hierarhical cluster analysis of groups of vectors It seems that you have already groups defined. Discriminant analysis would probably

howdy R friends, I've searched CRAN but to no avail... I'm trying to use mva's hclust and print out for say 10 clusters in batch. How do I do this? It's unclear if I can use cutree. thanks, John Strumila -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

I want to do hierarchical cluster analysis to compare 10 groups of vectors with five vectors in each group (i.e. I want to make a dendogram showing the clustering of the different groups). I've looked into using dist and hclust, but cannot see how to compare the different groups instead of the individual vectors. I am thankful for any help. Anders

Dear R I recently asked for a cluster analysis Using * cluster.results <- hclust(iris.dist, method="complete") * but nothing happened i.e the previous scatterplot matrix still showed up whereas I was expecting a dendogram. Could it be that because I had used cutree before on the scatter plots that it somehow mucked it up. I tried detach then attach and commenced making the data

Hi, I am new at R, and I need some help with some basic stuff. I want to do clustering of data. It works perfectly, but now I want to export my file form R to my Linux directory. The problem is that the file is generated only with the cluster numbers, but it does not carry over the identifiers. Let me show you what I did : 1. demo<-read.table("my_table", sep=",",

I am doing a cluster analysis with hclust. I want to get hclust to output the Hotelling's T squared statistic for each cluster so I can evaluate is data points should be in a cluster or not. My research to answer this question has been unsuccessful. Does anyone know how to get hclust to output the Hotelling's T squared statistic for each cluster? Mike [[alternative HTML version

Hi, I'm doing hierarchical clustering, and want to export my dendrogram to a tree-viewing/editing software. I can do this by converting the data to Newick format (hc2Newick in ctc package), but I can't get branch lengths to show in the resulting phylogram. I figured it might help to convert my hclust object into a phylo object (as.phylo in ape package), but the following lines give me

I have Windows XP Professional Version 2002 and the R-Version 2.1.1. I did cluster analysis with the cluster package and the agnes (method = ?ward?). The results are satisfactory. But the dendrogram of agnes is confused to work with the results. Is there a tool, I can get a clear arrangement of the results for the cluster analysis. For example a matrix with different numbers for each group.