similar to: Interpreting the result of 'cutree' from hclust/heatmap.2

Hello R-Helpers, I have a question about extracting the clusters of genes after we make the heatmap (say ht4) using the heatmap.2 function. Basically, I want to get the clusters which are shown as row dendrogram in the heatmap. I understand that ht4$rowDendrogram is an object of dendrogram and it containes details of all the nodes and branches, but lets say I want to know the number of clusters

Hi, I am a beginner for R. I had use gplots to generate a heatmap as following: >heatmap.2(matrix, col=topo.colors(75), dendrogram="column", Rowv=FALSE, trace="none", key=TRUE, keysize=0.8, density.info="none", cexRow=0.2, cexCol=0.6) It work well. It generate heatmap whith rcolumn clustering dendrogram and I can export a very nice graph. But I don not know how

Dear R helpers,   Following is a R script I am using to run the Fast Fourier Transform. The csv files has 10 columns with titles m1, m2, m3 .....m10.     When I use the following commands, I am getting the required results. The probelm is if there are 100 columns, it is not wise to define 100 commands as fk <- ONS$mk and so on. Thus, I need some guidance to write the loop for the STEP A and

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

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)

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

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

I would like to draw horizontal or vertical lines on a heatmap to highlight the clusters at some specified cut depth of the dendrogram. As a hacked example, the following code would work if I could set the coordinates of the top and bottom of the false color image correctly (ymin and ymax), but the correct values seem to depend on the output device and its size. I realize that heatmaps use a 2x2

Good afternoon, After cuting a hierarchical tree using cutree(), how to check correspondances between classes and branches? This is what we do: srndpchc <- hclust(dist(srndpc$x[1:1000,1:3]),method="ward") #creation of hierarchical tree plclust(srndpchc,hmin=20000) #visualisation srndpchc20000 = cutree(srndpchc,h=20000) #returns 4 classes table(srndpchc20000 ) srndclass20000 =

I've been using heatmap(), hclust(), and cutree(), and I'm trying to figure out the column labels of the left (as opposed to the right) cluster. Using cutree(x, k=2), I get two clusters labeled 1 and 2. How do you figure out if cluster 2 is the one associated with the left cluster on the heatmap (instead of manually going to the heatmap)? Thanks, Andrew Andrew Yee, MD MGH Cancer Center

I am using "heatmap" to cluster genes in microarrays. It works fine with 100~200 genes. But when I draw a heatmap with 600 genes, I can't read a clustering tree well. Maybe I will be able to read it by dividing it into several subtrees using a function such as "subtree". I found "subtree" in Splus, but not in R. Is there a similar function in R? Or, without it,

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 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, Can someone please guide me towards how to produce "heatmap" output from the output of "hclust" run prior to the actual "heatmap" call? I have some rather lengthy clustering going on and tweeking the visual output with "heatmap" recalculating the clustering every time is not feasible. Thanks, Joh

Dear list, I am using heatmap.2(x) to draw a heatmap. Ideally, I want to the matrix x clustered only by columns and keep the original order of rows unchanged. Is there a way to do that in heatmap.2()? Thanks a lot! Any suggestions will be appreciated! Best, Allen [[alternative HTML version deleted]]

Good afternoon, I ran heatmap and hclust on the same matrix x (strictly, I ran heatmap(x), and hclust(dist(t(x))), and realized that the two dendrograms were slightly different, in that the left-right arrangement of one pair of subclusters (columns) was reversed in the two functions (but all individual columns were grouped correctly). Looking through the code for heatmap as a most definite

I am making heatmaps for a dataset (~ 300*600 matrix) with the following R script (I am not familiar with R and this is the first time I am using it). library("gplots") library("Cairo") mydata <- read.csv(file="data.csv", header=TRUE, sep=",") rownames(mydata)=mydata$Name mydata <- mydata[,2:297] mydatamatrix <- data.matrix(mydata) mydatascale

Hi all, The function heatmap uses the functions dist and hclust with default parameters. How to change these parameters? For example, i want to use the ward criterion for hierarchical clustering with binary distance. Best regards, Olivier.

Hi Sorry if this is in the help :-S I've looked at example(dendrogram) and though it gives some indication of what I want, it doesn't do all. OK, so here is what I want to do: draw a tree, and then have an action, on user-click, to either draw a sub tree or a plot of the data. I also want users to be able to search for a particular label and have it highlighted on the tree, say in

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")