similar to: pvclust warning message

Hi, I am new to clustering and was wondering why pvclust using "maximum" as distance measure nearly always results in p-values above 95%. I wrote an example programme which demonstrates this effect. I uploaded a PDF showing the results Here is the code which produces the PDF file: ------------------------------------------------------------------------------------- s <-

Hello all, I posted a question to this list last week and received no response. I am unsure if this means no-one knows the answer or if I posed the question badly. I'm going to assume I posed the question badly and try again. I am new to R so it is quite likely it's a very naive question, however if there is something blindingly obvious that I am missing or if there is another resource I

Hi all I am writing to you with a question regarding the pvclust package. And yes, before the usual people produce their usual contact-the-package-maintainers line, ye, I tried that but the emails one can find on the web either bounce or are not responded to. Also, yes, this error has already been reported as a bug but been shot down as not reproducible

Good morning, I am analyzing a dataset composed by 364 subjects and 13 binary variables (0,1 = absence,presence). I am testing possible association (co-presence) of my variables. To do this, I was trying with cluster analysis. My main interest is to check for the significance of the obtained clusters. First, I tried with the pvclust() function, by using method.hclust="ward" and

Hi all, I'm new to R and I'm struggling to decipher an error message. Briefly, I am trying to use the pvclust package to do hierarchical clustering of some CGH data. The data is from the Progenetix CGH database. It is arranged as a table where each column is a single case and each row is a single chromosome band. The value in each cell is either 0, 1, 2, or -1. Corresponding to no change,

Hi, I have a microarray dataset of dimension 25000x30 and try to clustering using hclust(). But the clustering on the rows failed due to the size: > y<-hclust(dist(data),method='average') Error: cannot allocate vector of size 1.9 Gb I tried to increase the memory using memory.limit(size=3000), still got the same error. I also tried agnes() from cluster package and pvclust() from

I would like to get an hierarchical clustering tree with bootstrap values indicated on the nodes, as in pvclust. The problem is that I have only distance matrix instead of the raw data, required for pvclust. Is there a way to get it? fit1 <- hclust(dist) # an object of class '"dist" plot(fit1) # dendogram without p values library(pvclust) fit2 <- pvclust(raw.data,

Dear All I'm using PVClust to perform hierarchical clustering, for the output plot I can control most of the graphical I need, however the plot is large and I would like to split it vertically into two panels one above the other. Is there a way to plot only part of a PVClust plot, I tried to convert it to a dendrogram with result2 = as.dendrogram(result) however I get the error message

Is there a way to assign color to nodes as with hclust/as.dendrogram/dendrapply when using pvclust? The problem is that as.dendrogram isn't working on the pvclust objects. library(pvclust) pvc <- pvclust(matrix, nboot=1000) plot(pvc) -- View this message in context: http://www.nabble.com/Node-colors-in-pvclust-tp24405329p24405329.html Sent from the R help mailing list archive at

I want to classify bipolar neurons in human cochleas and have data of the following structure: Vol_Nuc Vol_Soma 1 186.23 731.96 2 204.58 4370.96 3 539.98 7344.86 4 477.71 6939.28 5 421.22 5588.53 6 276.61 1017.05 7 392.28 6392.32 8 424.43 6190.13 9 256.41 3850.51 10 249.17 3118.14 11 276.97 3037.29 12 295.30 3703.76 13 314.43 5265.97 14 301.15 5781.73 I

Hi, if you look at the first image (Image1) you see that there are 2 main clusters 7 and 8 I wanted to use pvclust to calculate a p-value whether these clusters are due to chance or statistically significant. Unfortunately pvclust does not provide a p-value for the first brunch (7 and 8). So I added a row to my matrix which is very different to the rest of the data to create an additional

Hello everyone! My data is composed of 277 individuals measured on 8 binary variables (1=yes, 2=no). I did two similar cluster analyses, one on SPSS 18.0 and one on R 2.9.2. The objective is to have the means for each variable per retained cluster. 1) the R analysis ran as followed: > call data > dist=dist(data,method="euclidean") >

Hello, I have trouble with a data set that comprises 2136 lines of 20 columns. I would like to do a hierarchical clustering and I tried the following: ages.hclust <- hclust(dist(ages, method="euclidean"), "ward") but I get the following error message: Error: cannot allocate vector of size 17797 Kb When I try to do the dist() alone first without the hclust(), I get the

You should reply to the list, not just me, and even more because I cannot really help you!! My guess (but I don't know this package, and even less this function) is that pvclust() is expecting a matrix as the first argument. However, "cluster" is no data, it is a function. Why, I don't know. Take a closer look at ?pvclust, especially the "usage",

Hi all, I have some microarray data on 40 samples that fall into two groups. I have a value for 480k probes for each of those samples. I performed a t test (rowttests) on each row(giving the indices of the columns for each group) then used p.adjust() to adjust the pvalues for the number of tests performed. I then selected only the probes with adj-p.value<=0.05. I end up with roughly 2000

Hi there, I have been trying to use the "pvclust" package but have been having some difficulties. This is the first time I have used R so I am sure the mistake I am making is a basic one. The data I have is a distance matrix and I have been using the command; fit <- pvclust(cluster, nboot=1000, method.dist="euclidean") to try and perform hierarchical clustering with

Hi all! I'm new to R and don't know many about it. Because it is free, I managed to learn it a little bit. Here is my problem: I did a cluster analysis on 30 observations and 16 variables (monde, figaro, liberation, etc.). Here is the .txt data file:

The R function hclust is used to do cluster analysis, but based on R help I see no way to print the actual fusion distances (that is, the vertical distances for each connected branch pairs seen in the cluster dendrogram). Any ideas? I'd like to use them test for significant differences from the mean fusion distance (i.e. The Best Cut Test). To perform a cluster analysis I'm using: x

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 realize questions about packages should go to the package maintainer, but perhaps I have an old email address (suzuki3 at is.titech.ac.jp) Also I have both a general, and a specific, question. 1) General question: i've used pvclust before to assess significance of clusters and got reasonable results. However, on a new data set (see below) the results seem odd. I wonder if pvclust is a