similar to: Error in heatmap

Hi netters, I have a matrix X of the size (1000,100). The values are from -3 to +3. When I tried heatmap(X, distfun=function(c),dist(c,method="bin"),hclustfun=function(m),hclust(m,method="average")) I got the error message: Error: evaluation nested too deeply: infinite recursion / options(expressions=)? However, if I used default parameters for distfunction:

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 all, The function heatmap uses the functions dist and hclust with default parameters. How to change these parameters? For example, i want to use the ward criterion for hierarchical clustering with binary distance. Best regards, Olivier.

Dear R wizards, Hopeful someone can help me with what I believe is a pretty simple task. I pretty new to R so some (much) of the obvious escapes me. How do I get a distance matrix into heatmap? What do I tell distfun if what I'm trying to map is already an ordered distance matrix? I tried >heatmap(x, distfun=as.dist(x)) where x is the distance matrix but R gave me an error. Thanks in

Hi, I run into following error when using heatmap() for data matrix "xx". Any help is appreciated? "xx" contains many "NA"s. > hv <- heatmap(data.matrix(xx)) Error in hclustfun(distfun(if (symm) x else t(x))) : NA/NaN/Inf in foreign function call (arg 11) Thanks a lot. Yuhong

Hi, I am using the function heatmap(stats) to draw a microarray heatmap, columns are samples and rows are gene features. I did a 2D clustering during the heatmap drawing. The features and samples indeed cluster into several blocks both vertically and horizontally. I can get the index of re-ordered rows and columns after the heatmap drawing by typing the the return variable of the heatmap

Hi, I am using heatmap.2 of gplots to make heatmaps of my the attached file. I am giving my code for the same .. library(gplots) x=read.table("1.txt", header=TRUE) mat=data.matrix(x) heatmap.2(mat, col=greenred(75), Rowv=TRUE, Colv=TRUE, distfun = dist, hclustfun = hclust, dendrogram = c("both"), scale = c("row"), na.rm=TRUE, trace="none",

Hello does anyone know what algorithm is used to produce the hierarchical clustering in the gplots package using the function heatmap.2? I think it may be the complete linkage clustering algorithm, but I can't find a source that seems reliable. Thank you and sorry if I posted this in the wrong place. If I have, please let me know and I will move it to the appropriate list. -- View this

I have written a wrapper for heatmap.2 called heatmap.w.row.and.col.clust which auto-generates breaks using breaks<-round((c(seq(from=(-20 * stddev), to=(20 * stddev))))/20, digits = 2) #(stddev in this case = 2.5) This has always worked well in the past but now I am getting an error that non-finite breaks are being generated. Drilling down, it seems that my wrapper is generating finite

Hello, I have come across some unexpected behaviour of the function heatmap in the stats package. This looks like a bug to me, but I might have misunderstood something. When calling the function in symmetric mode, the ColSideColors are plotted correctly, but RowSideColors appear in reverse order. This code (modified from the example on the help page) demonstrates the problem: cU <-

Hi, I am having troubles with heatmap(). I have a matrix containing pairwise distance values and I want to plot this matrix with heatmap. I wonder now what distfun is for. Is a distance matrix computed from my initial matrix again and then plotted? cheers, andreas

Hi,   I need to generate a heatmap on a square matrix and wouldn't want to reorder the columns and the rows on the heatmap display.    I have used the options Rowv=NULL and Colv=NULL but doesn't seem to work. Following is a snippet of the heatmap function i am using. args <- commandArgs(); inputfile <- args[2] imgfile   <- args[3] bitmap(imgfile, height=15, width=15, res=100,

Hi, Can someone please guide me towards how to produce "heatmap" output from the output of "hclust" run prior to the actual "heatmap" call? I have some rather lengthy clustering going on and tweeking the visual output with "heatmap" recalculating the clustering every time is not feasible. Thanks, Joh

Hi, I was wondering if someone in the mailing list has any insight into this segfault error that I consistently find when running a script containing heatmap() in R 2.8.1 and 2.8.0 on a Linux 64-bit machine. Some points: 1. This occurs when running heatmap(). 2. Interestingly, if I source() the script or copy and paste the script in its entirety, this error occurs. However, if I run the

Hi all (especially R-core) I suppose, With the introduction of the new functional programming functions into base I thought I'd ask for a Curry() function. I use a simple one that looks this: Curry = function(FUN,...) { .orig = list(...);function(...) do.call(FUN,c(.orig,list(...))) } This comes in really handy when using say, heatmap():

I have a data which contain some NA value in their elements. What I want to do is to **perform clustering without removing rows** where the NA is present. I understand that `gower` distance measure in `daisy` allow such situation. But why my code below doesn't work? __BEGIN__ # plot heat map with dendogram together. library("gplots") library("cluster")

Hi, Can anyone tell me how to set Z-score according to my own requirement as the below code is taking as per the file entries. Any help would be appreciable. library(gplots) x=read.table("final.txt", header=TRUE) mat=data.matrix(x) heatmap.2(mat, col=colorRampPalette(c("green","white","red"))(256), #col=greenred(75), Rowv=TRUE, Colv=FALSE, distfun = dist,

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)

heatmap.2 defaults to dist for calculating the distance matrix and hclust for clustering. Does anyone now how I can set dist to use the euclidean method and hclust to use the centroid method? I provided a compilable sample code bellow. I tried: distfun = dist(method = "euclidean"), but that doesn't work. Any ideas? library("gplots") library("RColorBrewer") test

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