search for: rowsidecolors

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 <- cor(USJudgeRatings) sideCols <- rainbow(ncol(cU)) heatmap(cU, symm = TRUE, distfun = function(c) as.dist(1 - c), ColSideColors=sideCols, RowSideColors=sideCols) Reversing t...

...!is.character(ColSideColors) || dim(ColSideColors)[1] != nc) stop("'ColSideColors' dim()[2] must be of length ncol(x)") lmat <- rbind(lmat[1, ] + 1, c(NA, 1), lmat[2, ] + 1) lhei <- c(lhei[1], 0.2, lhei[2]) } if (!missing(RowSideColors)) { #if (!is.matrix(RowSideColors)) #stop("'RowSideColors' must be a matrix") if (!is.character(RowSideColors) || dim(RowSideColors)[1] != nr) stop("'RowSideColors' must be a character vector of length nrow(x)")...

Hi there, I have two questions about heatmap.2 in gplot. My input is a simple square matrix with numeric values between 75 and 100 (it is a similarity matrix based on bacterial DNA sequences). 1. I can sort my input matrix into categories with rowsidecolors (in this case, very conveniently by bacterial taxa). I do a clustering and reordering of my matrix by Rowv=TRUE (and Colv="Rowv"). The question is now, can i combine the two features that the clustering/reordering is done only for submatrices defined by the vectors given in rowsidecol...

...= krc <krc at odin.mdacc.tmc.edu> >>>>> on Mon, 27 Jun 2005 21:55:37 +0200 (CEST) writes: krc> Full_Name: Kevin R. Coombes krc> Version: 2.1.0 krc> OS: Windows XP krc> Submission from: (NULL) (143.111.224.169) krc> When revC = TRUE and RowSideColors is set to a list of krc> colors in heatmap, then the image and dendrogram are krc> inverted, but the row-side color map does not krc> change. The following script illustrates the problem. krc> ############## krc> set.seed(1023) krc> # generate columns of t...

...ed? Can I adjust the title size in heatmap? Also, the position of the main title is at the very upper edge of the output and if I use a "\n" to stack the title the upper line is out of bounds and doesn't show up. I am outputting to pdf. Any help? Thanks, Mark heatmap(x = dataM, RowSideColors = RowSideColors, ColSideColors=ColSideColors, main = title, margins = c(50,50), scale= do.scale ,labRow=geneNames, labCol=colLabels, col = hmcol, cex.main = 1, cexRow = row.lab.mag, cexCol = col.lab.mag) > sessionInfo() R version 2.6.0 Under development (unstable) (2007...

Full_Name: Kevin R. Coombes Version: 2.1.0 OS: Windows XP Submission from: (NULL) (143.111.224.169) When revC = TRUE and RowSideColors is set to a list of colors in heatmap, then the image and dendrogram are inverted, but the row-side color map does not change. The following script illustrates the problem. ############## set.seed(1023) # generate columns of two different types d1 <- matrix(rnorm(100*6, rnorm(100, 0.5)), nrow=1...

...ding the option rm.na = TURE): > filename = "input_heatmap.txt" > g <- as.matrix(filedata) > fg <- rainbow(nrow(g), start=0, end=.3) > gg <- rainbow(ncol(g), start=0, end=.3) > hg <- heatmap(g, col = cm.colors(256), scale="column",na.rm = TRUE, + RowSideColors = fg, ColSideColors = gg, margin=c(5,10), + xlab = "Average per Species", ylab= "Pathways", + main = "heatmap(<Ka/Ks Average Data per Species>, ..., scale = \"column\")") Error in heatmap(g, col = cm.colors(256), scale = "column", na.rm = TRU...

...key in the upper left corner. Notice I have added side bars to the heatmap, but how could I move the color key below the image? ------ library(gplots) data(mtcars) x <- as.matrix(mtcars) rc <- rainbow(nrow(x), start=0, end=.3) cc <- rainbow(ncol(x), start=0, end=.3) res=heatmap.2(x, RowSideColors=rc, ColSideColors=cc)   Thank you very much,   Pingping Qu ----- Cancer Research And Biostatistics (CRAB) Seattle, WA 98101  ------- [[alternative HTML version deleted]]

...Can you help? I have been using: tmp <-read.table("Heat.txt",row.names=1,header=T) mydata <- data.matrix(tmp) rc <- rainbow(nrow(mydata),start=0, end=1) cc <- rainbow(ncol(mydata), start=0, end=1) hv <- heatmap(mydata, col = cm.colors(256), scale="column", RowSideColors = rc, ColSideColors = cc, margin=c(5,10), xlab = "Gene", ylab= "Species", main = "Heatmap", reorderfun = function(mydata,w) reorder(mydata,0.0:100.0), Colv=NULL, Rowv=T) Thnak you, Fearon Cassidy Department of Zoology Trinity College Dublin [[alternative HT...

...;) library(RColorBrewer) library(gplots) clrno=3 cols<-rainbow(clrno, alpha = 1) clstrs <- cutree(hc, k=clrno) ccols <- cols[as.vector(clstrs)] heatcol<-colorRampPalette(c(3,1,2), bias = 1.0)(32) heatmap.2(as.matrix(USArrests), Rowv=as.dendrogram(hc),col=heatcol, trace="none",RowSideColors=ccols) Nice, I can access 3 main clusters with cutree. But what about a situation when I perform hclust like hc <- hclust(dist(t(USArrests)), "ave") which I have to do in order to speed up the clustering process. This I can plot with: heatmap.2(as.matrix(USArrests), Colv=as.dendrog...

I generated a heatmap in R using the following commands: > mydata <- read.csv(file="Data.csv", header=TRUE, sep=",") > mydata <- mydata[rowSums(mydata[,-1]^2) >0, ] > rownames(mydata)=mydata$Name > mydata <- mydata[,2:253] > mydatamatrix <- data.matrix(mydata) > mydatascale <- t(scale(t(mydatamatrix))) > hr <-

I generated a heatmap in R using the following commands: > mydata <- read.csv(file="Data.csv", header=TRUE, sep=",") > mydata <- mydata[rowSums(mydata[,-1]^2) >0, ] > rownames(mydata)=mydata$Name > mydata <- mydata[,2:253] > mydatamatrix <- data.matrix(mydata) > mydatascale <- t(scale(t(mydatamatrix))) > hr <-

...n by this function. here is a reproducible example from the help page library(gplots) data(mtcars) x <- as.matrix(mtcars) rc <- rainbow(nrow(x), start=0, end=.3) cc <- rainbow(ncol(x), start=0, end=.3) hv <- heatmap.2(x, col=cm.colors(255), scale="column", RowSideColors=rc, ColSideColors=cc, margin=c(5, 10), xlab="specification variables", ylab= "Car Models", main="heatmap(, ..., scale=\"column\")", tracecol="green", density="density") This gives me a heatmap s...

...all: ##------------ Heatmap -------------- library(RColorBrewer) rc <- grey((nrow(x):1)/nrow(x)) heatmap(data.matrix(x[,1:4]), Rowv=NA, Colv=NA, scale='none',labCol=NULL, revC=TRUE, col = brewer.pal(9,'Greys'), ylab='time',margins=c(6,5), cexRow=1.5, cexCol=1.5, RowSideColors = rc) I end up with something like attached 'heatmap'. How can I change my call to: 1) most important: there are black strips on the right-hand side, these are the row numbers packed one on another. How to put there time points over, say, 500 sec epochs (1,500, 1000...) 2) put a scale on...

..."nbr" "nc" [45] "ncol" "notecex" "notecol" "nr" [49] "op" "retval" "revC" "rm" [53] "rowInd" "rowsep" "RowSideColors" "Rowv" [57] "scale" "scale01" "sepcolor" "sepwidth" [61] "sx" "symbreaks" "symkey" "symm" [65] "tmpbreaks" "trace" "tracecol&...

I am making heatmaps for a dataset (~ 300*600 matrix) with the following R script (I am not familiar with R and this is the first time I am using it). library("gplots") library("Cairo") mydata <- read.csv(file="data.csv", header=TRUE, sep=",") rownames(mydata)=mydata$Name mydata <- mydata[,2:297] mydatamatrix <- data.matrix(mydata) mydatascale

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

I have a data set with 6 variables and 251 cases. The people who supplied me with this data set believe that it falls naturally into three groups, and have given me a rule for determining group number from these 6 variables. If I do scaled.stuff <- scale(stuff, TRUE, c(...the design ranges...)) stuff.dist <- dist(scaled.stuff) stuff.hc <- hclust(stuff.dist)

...C() or .Fortran() had a lack-of-protection error if the registration information resulted in an argument being coerced to another type. o boxplot(x=x, at=at) with non finite elements in x and non integer at could not generate a warning but failed. o heatmap(x, symm=TRUE, RowSideColors=*) no longer draws the colors in reversed order. o predict(<ar>) was incorrect in the multivariate case, for p >= 2. o print(x, max=m) is now consistent when x is a "Date"; also the "reached ... max.print .." messages are now consistently using...

...C() or .Fortran() had a lack-of-protection error if the registration information resulted in an argument being coerced to another type. o boxplot(x=x, at=at) with non finite elements in x and non integer at could not generate a warning but failed. o heatmap(x, symm=TRUE, RowSideColors=*) no longer draws the colors in reversed order. o predict(<ar>) was incorrect in the multivariate case, for p >= 2. o print(x, max=m) is now consistent when x is a "Date"; also the "reached ... max.print .." messages are now consistently using...