similar to: Hierarchical clustering

Hi all, Here's an interesting (for me, at least!) problem I came across: I have a correlation matrix, let's say with 6 variables, A to F, as column headings and the same 6 as row headings. The matrix is filled with correlation coefficients. Therefore, the diagonal is all 1's, and each of the two triangles formed by the diagonal has the same 15 correlation coefficients. I need to

Hi, I am new to R...a recent convert from SAS. I have a dataset that looks like this: SEQ A1 A2 A 532.5 554.5 B 25.5 35.5 C 265.2 522.2 D 245.55 521.56 E 546.52 141.52 F 243.25 32.56 G 452.55 635.56 H 15.14 16.54 I 543.4 646.56 J 54.4 654.5 K 646.5 64.54 L 645.4 614.46 M 646.54 634.46 I want to make a histogram

Hi, I am making a dendrogram with 180 terminal values. Whether I keep it horizontal or vertical, it gives a 'squished' graph that refuses to be stretched beyond the window size and I cannot read the labels. (I'm using hclust and then plot to make the tree.) Is there a way to stretch the graph in R, or by exporting it somehow, so that I can read the 180 values and see what the results

Hey group, I have a problem of drawing dendrogram as the result of my program written in C. My algorithm is a approximation algorithm for single linkage method. AS a result I will get the following data: [Average distance] [cluster A] [cluster B] For example: 42.593141 1 26 42.593141 4 6 42.593141 123 124 42.593141 4 113 74.244206 1 123 74.244206 4 133 74.244206 1 36 So far I have used C to

Hello, I am new to the R package. After I use R to perform the hierarchical clustering, I am only interested in retrieving the leaf nodes that share the last common ancestors. As illustrated below, I'd like to retrieve (B, C) as a cluster and then (D, E) as another cluster. Any chance to do this in R? Thanks! BTW, I just subscribed to this list (not sure if the subscription is

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

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",

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

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,

Hi There, I'm working on some cluster analyses on a large data-set using hclust with Wards method and Manhattan (city block) distance measures. I've created dendrograms to illustrate the clustering criteria, but would like to create a plot to examine for the classic elbow criterion to use in determining the best number of clusters. Ideally I'd like to plot percent variance explained

Hi, I''m using heatmap.2 to cluster my data, using the centroid method for clustering and the maximum method for calculating the distance matrix: library("gplots") library("RColorBrewer") test <- matrix(c(0.96, 0.07, 0.97, 0.98, 0.50, 0.28, 0.29, 0.77, 0.08, 0.96, 0.51, 0.51, 0.14, 0.19, 0.41, 0.51), ncol=4, byrow=TRUE)

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

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

Dear Dr. Liaw Andy: I have a few more questions about your heatmap function. actually heatmap is what I am looking for. heatmap(x, Rowv, Colv, distfun = dist, hclustfun = hclust, add.expr, scale=c("row", "column", "none"), na.rm = TRUE, ...) my data is a XNEW, > dim(XNEW) [1] 554 335 554 genes, 335 samples. now I want to use 1-CORR as a distance

Thanks a lot, Michael! I cc to R-help, where this question really belongs {as the 'Subject' suggests itself...} -- please drop 'bioconductor' from CC'ing further replies. >>>>> "michael" == michael watson (IAH-C) <michael.watson at bbsrc.ac.uk> >>>>> on Thu, 17 Jun 2004 09:16:59 +0100 writes: michael> OK, admittedly it

Hi, I'm using R on Windows and upgraded the computer memory to 4GB, as R was telling me that it is out of memory (for making heatmaps). It still says that the maximum memory is 1024Mb, even if I increase it using memory.limit and memory.size. Is there a way to permanently increase R's memory quota to 4GB? Please help. Many thanks, -DS. [[alternative HTML version deleted]]

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, I have some hydrochemical data from observation stations of a river network. The data set provides information about the river hierarchy, i.e. the order of the rivers (main river is 1st order, contributing is 2nd order, and contributing to 2nd is 3rd order... etc). Now I would like to use the hierarchical information to: a) plot a dendrogram of the observation stations b) perform some simple

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")

I'm using samba 3.5.6 + PDC and connected to LDAP directory In log level 1 there is many entries like this : Feb 18 18:13:42 samba smbd[21646]: getpeername failed. Error was Transport endpoint is not connected Feb 18 18:13:42 samba smbd[21646]: write_data: write failure in writing to client 0.0.0.0. Error Connection reset by peer Is it a problem ? or just an informative event ? Feb 18