similar to: Flip axis on hist2d plot

The following code produces a heatmap based on normalized data. I would like to mirror x and y axis for this plot. Any idea how to do that? require("gplots") x <- rnorm(500) y <- rnorm(500) hist2d(x, y, freq=TRUE, nbins=50, col = c("white",heat.colors(256))) Best, Ralf

I created a 2d histogram using gplots' hist2d: hist2d(x,y, freq=TRUE, nbins=50, col = c("white",heat.colors(256))) rug(x, side=1) rug(y, side=2) box() Now I would like to reverse the Y-axis, tried to use ylim=rev(range(1:400)) but seems not to work. Any ideas? Ralf

Hello, I have created two histograms with: hist2d(gps2, nbins=200, col = c("white",heat.colors(16))) Both of them have the same range and the same number of bins. Now I would like to compare them bin by bin and plot the results. Could someone please tell me how to do that. I searched the man pages and the web, but couldn't find anything. Thank you very much. Phil

Dear R users, I have a question regarding how to make row labels readable in a heat map. I have successfully made a heat map using function "heatmap.2" in the package "gplots". However, as there are many rows in the heat map, I have difficulties labeling them (heatmap.2 provides a parameter "labRow" to label the row names, but as I have too many rows, I can not make

Hi, what i need is as the example i attached in the box plot. As you can see, the boxplot have margins and it kind of follow the coding I've added, but, it does not happen for the heat map. Could you help me with this.. Thanks in advance. the following is the coding i've used: # Draw the heatmap # heatmap.r # # Purpose: Create a heatmap # # Input: Data matrix as

I am having difficulty installing packages. For example, here I have tried to install "gplots" but to no avail. I have tried multiple mirrors and different packages (errbar) but after installation I seem to be unable to access any of the commands or help pages. I am a little concerned about the 'lib' missing message but this has been present for previous successful package

Hey, I am still working on my heat map (for those who are read my previous post about row.names)… Now, I would like to save my heat map.2 in .png or .tiff in order being able to work on the picture in photoshop, but it doesn't work. I'am using (as I have found on some forum) > png("heatmap.2.png) # and it just doesn't work. when I try doing it with::

Esteemed R-users, heatmap.2() is yielding an inappropriate key based on my colors and break-points. In the reproducible example below, the key is inappropriate (to me) because- 1. 'Orange' is simply not represented in the key, despite its prescence in the heatmap. 2. The proportions of the key are clearly out, ie., my largest bin, (0.1 - 0.2) is half the range, but this bin (colored

Hi, I am drawing a heat map using gplots of R package. The file (new4) is having values 0 and 1 only. library(gplots) library(marray) x=read.table("new4", header=TRUE) mat=data.matrix(x) heatmap.2(mat, col=colorRampPalette(c("black","red"))(256), #col=greenred(75), Rowv=TRUE, Colv=TRUE, distfun = dist, hclustfun = hclust, dendrogram = c("row"), scale =

Announcing gplots 2.5.0 --------------------------------- gplots provides additional plotting functions, including several enhanced versions of base R functions. Provided functions include: balloonplot, bandplot, barplot2, boxplot.n, colorpanel, heatmap.2, hist2d, lowess, ooplot, overplot, plot.lm2, plotCI, plotmeans, qqnorm.aov, residplot, rich.color, sinkplot, smartlegend, space,

Announcing gplots 2.5.0 --------------------------------- gplots provides additional plotting functions, including several enhanced versions of base R functions. Provided functions include: balloonplot, bandplot, barplot2, boxplot.n, colorpanel, heatmap.2, hist2d, lowess, ooplot, overplot, plot.lm2, plotCI, plotmeans, qqnorm.aov, residplot, rich.color, sinkplot, smartlegend, space,

Dear R-wizards, I'm trying to plot "binned scatterplots", or 2d histograms, if you wish, for a number of groups by using the lattice functionality it works fine for one group at a time, and probably I could find a work-around, but I prefer to do it the elegant way here's an example of what I want, what I tried and where it goes wrong: require(gregmisc) require(lattice) #toy

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",

Dear All, I want to plot a heat map with annotated columns. Both functions heatmap (stats) and heatmap.2 (gplots) can plot a horizontal side bar that can be used to visualize a categorical variable. In addition to a categorical variable, I would like to visualize a continuous variable. This could be done by small bars, a curve or simply numbers above the columns. (The Sample names are already

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 <-

Hola a todos, Estoy trabajando con la función heatmap.2() de la libreria ggplots. A continuación encontrarán un ejemplo de la estructura de mis datos y el código para generar el gráfico que me gustaría modificar: # Datos set.seed(123) x <- matrix(rnorm(8*30), ncol = 8) rownames(x) <- paste(''GM10A'',1:30,sep="") colnames(x) <-

Hello R-Community, I am a rookie in R and I am fascinated with the power of bio computing by R. I am analysing gene expression data from Real time PCR. I have used absolute gene quantitation to measure gene copy number in all my transcripts. All my data has been normalised them to a housekeeping gene, which is constitutive expressed. My problem is as follows. After normalising some of the genes

I'd like to use the hist2d function. What library contains it? Thanks! Simon Firestone Economist, Fair Lending Enforcement Division of Consumer and Community Affairs Federal Reserve Board Washington, DC 20551 simon.b.firestone@frb.gov (202) 785-6056 [[alternative HTML version deleted]]

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

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")