similar to: plotting hclust dendrograms

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

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

Dear List, My dataset is as below: I am using library(cluster) hierarchical clustering on these data. If i try to plot these i couldn't see the partitions clearly, > dd<-hclust(dist(DataSetS01022Full), "ave") > Warning message: >NAs introduced by coercion >(dn<-as.dendrogram(dd)) >plot(dn) please find the link on the plot : http://roughjade.blogspot.com

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

Hello, a. when I use hclust with the methods media, centroid, and mcquitty, and plot the results, the dendrograms have lines that are crossing each other. Is this ok? b. My next question refers to plot.dendrogram: How can I use parameters as "hang" or "cex" here? E.g. for st <- as.dendrogram(subtreeshc[[x]]) I would like to have something like this, where cex and hang

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

Hi All Not sure if this a bioconductor question or general R mailing list so apologies if this has gone to the wrong one................. When plotting dendrograms created by hclust you can "identify" clusters by clicking on the graphics and returning a list of what is contained in each cluster. However I'd like to be able to "zoom in" on specific clusters and plot

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

I would like to be able to exert certain types of control over the plotting of dendrograms (representing hierarchical clusterings) that I think is best achieved by modifying the dendrogram object prior to plotting. I am using the "dendrogram" class and associated methods. Define the cluster number of each cluster formed as the corresponding row of the merge object. So, if you are

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

Hello all, I manually created an hclust object. Now I am looking to reorder the leafs so they won't intersect with each other, and would be happy for advises on how to do that. Here is an example code: #------------------------------------- a <- list() # initialize empty object # define merging pattern: # negative numbers are leaves, # positive are merged clusters (defined by row

Hi, I have produced a dendrogram of categorical data in R using the hclust function, although the input was a dissimilarity matrix produced in SAS, as I have defined my own distances. The dendrogram is fine and I can view and use this. However, I was wondering if there is a method by which I can find out the optimal place to place groups, rather than relying on my visual analysis? I don't

Dear list, I am trying to plot a radial dendrogram using the ape package, which requires my data to be of class 'phylo'. Currently I have my dendrogram stored as an object of class 'dendrogram' which was produced from an outside bit of C code, but was made into an object of class 'igraph.eigenc' and converted to a dendrogram using 'as.dendrogram()' from the igraph

I have tried to use rect.hclust() to draw a rectangle around a set of leaves, but am running into trouble. The rect.hclust() is drawing two rects instead of one, and of the wrong size: -------------------- scoreClusterObj <- hclust(scoreDistanceObj, method=clustMethod) order <- scoreClusterObj$order orderedLabels <- rep(0, length(order)) for (orderIndex in 1:length(order)) { # this

Hi all, I've been doing some investigation to see if it is possible to implement an hclust/dendrogram related requirement that I've been given. So far ?hclust and a lot of googling haven't provided the information I'm looking for (I've been using R sporadically for a year). The requirement I have is to: On a dendrogram plot, draw points at various merge locations, based on

Hi, I'm using the latticeExtra package's dendrogramGrob function to create a grob with both a dendrogram and a covariate bar (via the 'add' parameter). When the dendrogram has very short branches at its leaves, it appears as a line and becomes impossible to see when placed next to the covariate bar. For example: > x <- outer(-5:5, -5:5, "*") + matrix(nrow = 11,

Hello all I've been using the hclust and as.dendrogram objects for hierarchical clustering. The problem I have is that my sample set is now so large (circa 500 points) that it isn't possible to view the leaf nodes. I'd like to be able to zoom in on specific areas of the graph by selecting a region with the mouse. I've deduced from trial and error that the xlim and ylim

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

Ladies and Gentlemen, As Johan Lindberg points out, the documentation for handling dendrograms is sparse....Does anyone know who is responsible for or working on development of tree methods and objects? I've written a couple of scripts for my own use to translate between parenthetical (A(B(CD))) or binary A00 B10 C11 D11 tree formats and cluster objects in R, but as an inexperienced

Hello all, I am using libraries (mva,cluster) to produce dendrograms. With 1000 examples the dendrogram gets too crowded, and i am wondering whether there is an option (which i cannot find) to set the number of leaf nodes, like in matlab, and return the plot and the assignment map examples -> leaf nodes. Any suggestion is appreciated. Thanks Edo