similar to: Dendrogram for agglomerative hierarchical clustering result

Dear R users, I have created data for hierarchical agglomerative cluster analysis which consist of the merging pairs and the agglomeration heights, e.g. something like my.merge <- matrix(c(-1,-2,-3,1), ncol=2, byrow=TRUE) my.height <- c(0.5, 1) I'd like to plot a corresponding dendrogram but I don't know how to convert my data to achieve this. Is it possible to create a

Dear R-users, I need some help concerning the plotting of dendrograms for hierarchical agglomerative clustering. The agglomeration niveau of each step should be displayed at the branches of the dendrogram. For this I need the x/y coordinates of the branch-agglomerations of the dendrogram. The y-values are known (the heights of the agglomeration), but how can I get the x-values? > mydata

Hi, How to plot the dendrogram or tree for kmeans, like we do for hclust ? [[alternative HTML version deleted]]

Dear R user, I am a biochemist/bioinformatician, at the moment working on protein clusterings by conformation similarity. I only started seriously working with R about a couple of months ago. I have been able so far to read my way through tutorials and set-up my hierarchical clusterings. My problem is that I cannot find a way to obtain information on the rooting of specific nodes, i.e. of

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

Hello all, I wish to compare two dendrograms (representing Hierarchical Clusterings). My problems are several: 1) how do I manually create a dendrogram object ? That is, how can I reconstruct it as an "hclust" object that creates such a dendrogram, when all I have is the dendrogram image (but don't have the underlaying distance matrix that produced it) ? I see that there is a

Hey Everyone! I wanted to carry out Hierarchical clustering using distance matrices i have calculated ( instead of euclidean distance etc.) I understand as.dist is the function for this, but the distances in the dendrogram i got by using the following script(1) were not the distances defined in my distance matrices. script: var<-read.table("the distance matrix i calculated",

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Hello All, i've a set of observations that is in the form : a, b, c, d, e, f 67.12, 4.28, 1.7825, 30, 3, 16001 67.12, 4.28, 1.7825, 30, 3, 16001 66.57, 4.28, 1.355, 30, 3, 16001 66.2, 4.28, 1.3459, 13, 3, 16001 66.2, 4.28, 1.3459, 13, 3, 16001 66.2, 4.28, 1.3459, 13, 3, 16001 66.2,

Dear all, i performed a clusteranalysis - which worked so far... i plotted the dendrogram and sooo many branches, a rough sketch would be enough ;) i tried max.levels therefore which worked, but not for the plot... i used the following plot(hcd,nodePar =nP, str(hcd,max.level=1)) the output on the terminal was: --[dendrogram w/ 2 branches and 196 members at h = 2.70] |--[dendrogram w/ 2

Dear list members, I have been using R to create a heatmap where my data has continous variables from 0 to 100. When I create the heatmap, although the branches are correct, they do not order themselves so that the row with the most zeros is at one end and the row with the most 100s is at the other, which is what I would like them to do, so as to create a colour gradient down the graphic. I have

Hi all, This is the first time I'm writing to R-devel, and this time I'm just asking for the purpose for a certain line of code in stats::as.hclust.dendrogram, which comes up as I'm trying to fix dendextend. The line in question is at line 128 of dendrogram.R in R-3.3.3, at stats::as.hclust.dendrogram: stopifnot(length(s) == 2L, all( vapply(s, is.integer, NA) )) Is there any

Hi all, ok, i know i can cut a dendrogram, which i did. all i get is three objects that a dendrograms itself. for example: myd$upper, myd$lower[[1]], myd$lower[[2]] and so on. of course i can plot them seperately now. but the lower parts still have hundreds of branches. i?ll need a 30 " widescreen to watch the whole picture. what i?d like to is group the lower branches , so that i get a

Dear I am using the 'as.dendrogram' function from the 'stats' library to convert from an hclust object to a dendrogram with a dataset of size ~30000 (an example code is below). I need the dendrogram structure to use the "dendrapply" and "attributes" functions and to access the child nodes, I do not need any of the plot properties. The problem is that it

Hi All, i've problem to understand how to work with R to generate a hierarchical clustering my data are in a csv and looks like : idcode,count,temp,sal,depth_m,subs 16001,136,4.308,32.828,63.46,47 16001,109,4.31,32.829,63.09,49 16001,107,4.302,32.822,62.54,47 16001,87,4.318,32.834,62.54,48 16002,82,4.312,32.832,63.28,49 16002,77,4.325,32.828,65.65,46 16002,77,4.302,32.821,62.36,47

Hi all, Can someone tell me how to justify (right or left) the labels on the branches of a dendrogram tree? I have produced a dendrogram via agnes and plotted it with pltree. The dendrogram terminal branch labels seem to be centre-justified by default and I was hoping to change this to left justification. Thanks, Duncan ***************************************** Dr. Duncan Mackay School of

Hi, I am clustering objects using the agnes() function and the UPGMA clustering method (function = "average"). Everything works well, but apparently something is wrong with the dendrogram. For example: x<-c(102,102.1,112.5,113,100.3,108.2,101.1,104,105.5,106.3) y<-c(110,111,110.2,112.1,119.5,122.1,102,112,112.5,115) xy<-cbind(x,y) library(cluster) UPGMA.orig<-agnes(x)

Hello, Is it possible to remove those extra margins on the "sample" axis from plot.dendrogram: par(oma=c(0,0,0,0),mar=c(0,0,0,0)) ddr<-as.dendrogram(hclust(dist(matrix(sample(1:1000,200),nrow=100)))) stats:::plot.dendrogram(ddr,horiz=F,axes=F,yaxs="i",leaflab="none") vs. stats:::plot.dendrogram(ddr,horiz=T,axes=F,yaxs="i",leaflab="none")

I'm clustering rather large data sets and would like to cut the dendrograms to get a better view of specific components. I calculate the dissimilarity matrix using daisy() because I have a mixture of variable types: factors, ordered factors and numerical variables. If I want one dendrogram, I use agnes() for the agglomerative nesting and pltree() to draw the dendrogram. That way, I get the

Dear All, I have a cluster object based on a dissimilarity matrix from about 1,100 cases and wish to know whether anyone can think of any tips to display some form of graphical output which would give some sense of the similarity between the cases. A standard form of dendrogram would be fine, but with so many cases the dendrogram on the standard devices (R-2.20 on NT4) is very compact