similar to: Memory issues

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

I want to get a 64-bit machine/OS system so I can put 16Gb of RAM in it. As first I assumed that I would have to use the 64-bit version of R to make use of the 16Gb of RAM, which would mean that I would use the Linux version of R. But I have heard many posters say they run the 32-bit version of R on a 64-bit machine/OS. So my questions, in Windows 64-bit, how much memory would be available to

Hi all, I've got a set of gene expression data, and I'm plotting several heatmaps for subsets of the whole set. I'd like the heatmaps to have the same color distribution, so that comparisons may be made (roughly) across heatmaps; this would require that the color distribution and distance functions be based on the entire dataset, rather than on individual subsets. Does

I thought I'd share this with the list since it appears to provide a quick fix to some memory problems, and I haven't see it discussed in relation to R. To reallocate virtual memory from kernel-mode to user-mode in 32-bit Vista or Windows 7 one can use the increaseuserva boot option value. See http://msdn.microsoft.com/en-us/library/aa906211.aspx On my 4GB Vista machine, R is now able to

The answer is "don't do that" because that function abuses par. Use lattice or ggplot2 with grid graphics to plot multiple heatmaps. https://stackoverflow.com/questions/15114347/to-display-two-heatmaps-in-same-pdf-side-by-side-in-r -- Sent from my phone. Please excuse my brevity. On July 23, 2017 5:11:32 AM PDT, Brian Smith <bsmith030465 at gmail.com> wrote: >Hi, >

Hi, I was trying to use par(mfrow) to put 4 heatmaps on a single page. However, I get one plot per page and not one page with 4 plots. What should I modify? Test code is given below: test = matrix(rnorm(60), 20, 3) pdf(file='test.pdf',width=10,height=8) par(mfrow=c(2,2)) heatmap(test) heatmap(test) heatmap(test) heatmap(test) dev.off() thanks! [[alternative HTML version deleted]]

Hi, I am running R 2.0.1.1. on Windows. It is a Dell Dimension with a 3.2 Ghz Processor and 4Gb RAM. When using the ReadAffy() function to read in 97 arrays, I get the below error messages: Error: cannot allocate vector of size 393529 Reached total allocation of 1024Mb: see help(memory.size) When I use the comman "memory.limit(size=4000)" to increase the memory size to the

Hi, I'm trying to save heatmaps as PDFs. However, the PDF version of the heatmaps (Heatmap_CAFvsTNF_run2.pdf) is blurred when compared to its counterpart, which was saved manually by using the software "Grab" (Heatmap_CAFvsTNF_run2.tiff). -----R code-------- sample_output <- "stroma_run2" filename <-

Basically, I have the location data for about 1,000 pitches. I can get them to show up correctly on normal plots, but I am genuinely messed up on heatmaps. > location <- read.csv('C:/Users/William/Downloads/09Location.csv') > location <- as.matrix(location) Like I said, that can get a plot fine. Should I use image or heatmap? For the record, I want something like

Dear all, I've been trying to find how to compare tow different heatmaps but I'm having trouble getting the colors bar to be the same. I'm doing something like the following: library(gplots) dat<-cor(matrix(rnorm(100, m=10), nrow=10)) mat<-cor(matrix(rnorm(100), nrow=10)) dev.new() heatmap.2(mat, Rowv=NA, Colv=NA, col=redgreen(75), symm=TRUE, trace="none",

Hi, I'm stuck with parsing data into R for heatmap representation. The data looks like: 1 id1 x1 x2 x3 .... x20 2 id1 x1 x2 x3 .... x20 3 id1 x1 x2 x3 .... x20 4 id1 x1 x2 x3 .... x20 ......... 348 id2 x1 x2 x3 .... x20 349 id2 x1 x2 x3 .... x20 350 id2 x1 x2 x3 .... x20 351 id2 x1 x2 x3 .... x20 ......... The data is sorted for the IDs (id1,id2 .....id40) and I like to

Hello All, I am trying to get cluster heatmaps using R from Java in my application. I got the Rserve using which I am able to make TCP/IP connection to R. I am trying to send a double[][] array (say 5x8 dimensions) to R and convert it into matrix using as.matrix() function in R. Is it correct to do this? Can I directly pass this array to dist() function to generate the distance matrix ? if not

Using the heatmap function in mva, it seems to be hard to use different colors in the edges leading to different groups of objects, as commonly done in many heatmaps in the microarray graphics. Any suggestions? Thanks. max

Hello All, I have 2 matrices consisting of the same inputs, but having different outputs. I created a heatmap for both of them; the point is to compare them side by side. The best way to organize the inputs is to make sure that the order of the inputs are the same for both heatmaps. How would I go about making sure that the order of inputs of both heatmaps are the same? As it is right now, I can

Hello, I have a large (919 X 919), hierarchically clustered heatmap that I would like to read the labels off of. I have tried saving the figure in pdf format and enlarging it until I can see the labels, but if I make the labels small enough to read (so that they don't overlap) using cexRow and cexCol, they do not appear in the pdf. The limit seems to be anything below cexRow or Col = 0.06.

Hi, I'm trying to build some maps of the US by county that will have the following characteristics: Feature/Map Map 1 Map2 Both Broken out by county Yes Yes Yes Heatmaps of US Census Data for income by county Yes No Yes Heatmaps of US Census Data for race by county (recoded as white and &non-white, with each county color coded based on the majority) No Yes No Polygon

Dear R users, I am trying to print heatmaps in a loop (with a pause). Idea is to visualize changing correlations over time and for testing I wrote this simple (reproducible) code below. My problem is that levelplot() does not produce any output when I run the code (though heatmap does). Ideally I would like to use levelplot() as it produces a neat index on the side indicating the color and the

Hello! I looked for help through google and the help-files and spend several hours with trial and error, but didn't find a correct way. It's all about lines in a heatmap to separate different data block from each other to underline the significance of the found clusters! The heatmap is build like that: heatmap(X, Rowv=NA, Colv=NA, symm=TRUE, cexRow=0.3, cexCol=0.3) I switched the