similar to: hclust() memory issue

Dear all, I have run into a problem when running some code implemented in the Bioconductor panp-package (applied to my own expression data), whereby gene expression values of known true negative probesets (x) are interpolated onto present/absent p-values (y) between 0 and 1 using the *approxfun - function*{stats}; when I have used R version 2.8, everything had worked fine, however, after updating

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

Hi, I am trying to use 'GridR' package for the first time, and I'm running into a strange error from grid.check: > grid.check(gridFun) Error in exists(add) : invalid first argument After playing around in recover mode, I see that this because the variable 'add' created by grid.check is blank: Browse[1]> split[[1]][k] [1] " : " Browse[1]> add [1]

Hello everyone, I have a problem when loading the library: IlluminaHumanMethylation27k.db I installed the package from zip (from the Bioconductor website), and also installed all the packages it asked for. It went all succesfull: "package 'IlluminaHumanMethylation27k.db' successfully unpacked and MD5 sums checked" But when I am trying to load this library I get an error:

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 <-

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

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,

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

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",

hello, i'd be happy if someone could provide help with the following problem: i have a dist.matrix that comes from vegdist() function of the vegan package. the used method = "horn" is not accepted as argument in hvcluster(...,dist.method="..."). is there a way to incorporate the method "horn" in hvcluster()? thanks in advance! yours, kay -- View this

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

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

Hi all I am trying to perform the follwing: fit<-pvclust(wq, method.hclust="ward", method.dist="euclidean") but get a strange error message that I just cant figure out. Has anyone come across this? Any help would be most appricieated Error in hclust(distance, method = method.hclust) : NA/NaN/Inf in foreign function call (arg 11) In addition: Warning message: NAs

Hello, I am attempting to assign significance levels to a UPGMA cluster analysis as part my doctoral research. The pvclust function works well but doesn't include the similarity index I need (morisita's) as an option for computing a distance matrix. Morisita's is available in vegdist in the VEGAN library but I am having a hard time getting the vegdist function to "direct

Hello there, Here's a question regarding p-values on clusters produced by hierarchical cluster analysis. A web search led me to the program pvclust to tackle this problem. But when I run the problem I get strange results. The 'AU' (approximately unbiased) p-values are very different from the 'BP' values (ordinary boot-strap) p-values. The AUs commonly are in the 80-100

Or at least is seems that way to me. It's not a big problem, but the behavior doesn't match the documentation. (I think r-help is the place to report this. ) > x <- factor(1:5) > x.ro <- reorder(x, rnorm(5)) > is.ordered(x.ro) # should be FALSE according to ?reorder [1] TRUE > > x.ro <- reorder(x, rnorm(5), ordered=FALSE) > is.ordered(x.ro) # should be FALSE

Dear List, I have another question to bother you about how to do clustering. My data consists of 49 columns (49 variables) and 238804 rows. I would like to do hierarchical clustering (unsupervised clustering and PCA). So far I tried pvclust (www.is.titech.ac.jp/~shimo/prog/*pvclust* /) but I always had the problem like for R like "cannot allocate the memory". I am curious about what

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

Hello Folks. This must be a silly question with a (not) obvious (to me) answer. Consider this: tmp <- matrix(1:200, nrow = 20) vec <- 300:309 tmp[9,] <- vec # replacing one row works fine p <- c(3, 11, 17) tmp[p,] <- vec # replacing multple rows pastes the values down a column and recycles vec. What I want to do is replace multiple rows simultaneously at once. I suppose I can