similar to: Volcano Plot

Hello. My name is Akashah. i work at metabolic laboratory. From my study, i found that volcano plot can help a lot in my section.  i already studied about the volcano plot and get the coding to run in R software, unfortunately, there is may be something wrong with the coding. This is because  no graph appear, but no error (blue color text) was shown on the R console. Below is the coding for

HELLO, anybody... could you help me to check the below coding for volcano. what is the mistake? what the plot could not display? # volcano_plot.r # # Author: Amsha Nahid, Jairus Bowne, Gerard Murray # Purpose: Produces a volcano plot # # Input: Data matrix as specified in Data-matrix-format.pdf # Output: Plots log2(fold change) vs log10(t-test P-value) # #

hi dear R crew. may i request the script for volcano plot. if able, pls include any tips about volcano plot. thank you. [[alternative HTML version deleted]]

Can't installe packag maDB or limma. Error is shown as Using R version 2.13.1, biocinstall version 2.8.4. Installing Bioconductor version 2.8 packages: Is there any other way to draw volcano plot ? Thanks [[alternative HTML version deleted]]

Hello all, I was trying to make a volcano plot with some real data, using log2(ratio) vs. Z-value significance. However the scatter of the points is too less contrary to 'normal' volcano plots and I'm getting a sharp 'V' shaped plot. *Am I doing something wrong here?* The data(ratio) is available from pastebin: http://pastebin.com/m2Jss3qF data <-

Hello R-users, I am looking for an elegant way to calculate p-values for each row of a data frame. My situation is as follows: I have a gene expression results from a microarray with 64 samples looking at 25626 genes. The results are in a data frame with the dimensions 64 by 25626 I want to create a volcano plot of difference of means vs. ?log(10) of the p-values, comparing normal samples to

I'm new to R and some what new to the world of stats. I got frustrated with excel and found R. Enough of that already. I'm trying to test and correct for Heteroskedasticity I have data in a csv file that I load and store in a dataframe. > ds <- read.csv("book2.csv") > df <- data.frame(ds) I then preform a OLS regression: > lmfit <- lm(df$y~df$x) To

Hi Everyone, I am trying to use lmFit function; however, i cannot find it function anywhere. I have been trying to find the function in Bioconductor and elsewhere. I re-install bioconductor source, update package and update R as well. no luck Is there a command in R where i can just type, and it will download it for me? -- View this message in context:

Dear All, I was looking for the color index in?image function,?such as from topo.colors(n) and etc. but still never found it. For instance, from the help menu. ########################################### # Volcano data visualized as matrix. Need to transpose and flip # matrix horizontally. image(t(volcano)[ncol(volcano):1,]) # A prettier display of the volcano x <- 10*(1:nrow(volcano)) y

Hi R-help community, Can anyone tell me why, while using : x <- seq(as.Date("2001-01-01"),as.Date("2001-01-01") + nrow(volcano)-1,1) y <- seq(1, ncol(volcano),1) when I plot the volcano matrix with that command : filled.contour(x,y,volcano) the graph has a Date format on X-axis, ok ... ... but when adding a contour plot to the filled contour, using this

Do you know what steps I need to take to add a scale to a plot? I'm pulling my example out of "An Introduction to R: Software for StatisticalModelling & Computing" (see the R code around Figure 76). I would like to add a scale to the image produced by the following code.? I would like to the scale to list the distance?and units:? data(volcano) x <- 10*(1:nrow(volcano)) y

I try to send this message To Gordon Smyth at smyth at vehi,edu.au but it bounced back, so here it is to r-help I am trying to use limma, just downloaded it from CRAN. I use R 2.0.1 on Win XP see the following: > library(RODBC) > chan1 <- odbcConnectExcel("D:/Data/mgc/Chips/Chips4.xls") > dd <- sqlFetch(chan1,"Raw") # all data 12000 > # > nzw <-

My data: I have raw data points that form a logit style curve as if they were a time series. Which is to say they form 3 distinct lines with 3 distinct slopes in backwards z pattern. A certain class of my data looks essentially flat to the eye with marginal oscillation. What is important to me is the x value at which the state change is occurring, in other words, the break point Use of

Hi list, I wonder if anyone has had this experience with squishplot() in the TeachingDemos package. Taking the example from the ?image help page, library(TeachingDemos) x <- 10*(1:nrow(volcano)) y <- 10*(1:ncol(volcano)) layout(matrix(c(1,2,3,4),ncol=2,byrow=TRUE),height=c(2,1)) ## 1st plot op <- squishplot(range(x),range(y),1) image(x, y, volcano, col = terrain.colors(100)) par(op)

Hi! Whenever I save a graphic in ps/eps format generated by filled.contour or image, an undesired grid is added to it (not visible on the X11 screen). For example: postscript("volcano.eps") filled.contour(volcano,col=gray(seq(0,1,,50)),levels=seq(min(volcano),max(volcano),,50)) dev.off() Any ideia how to eliminate this grid? Thanks, Rachel [[alternative HTML version deleted]]

Hi there, I am trying to use linear regression to solve the following equation - y <- c(0.2525, 0.3448, 0.2358, 0.3696, 0.2708, 0.1667, 0.2941, 0.2333, 0.1500, 0.3077, 0.3462, 0.1667, 0.2500, 0.3214, 0.1364) x2 <- c(0.368, 0.537, 0.379, 0.472, 0.401, 0.361, 0.644, 0.444, 0.440, 0.676, 0.679, 0.622, 0.450, 0.379, 0.620) x1 <- 1-x2 # equation lmFit <- lm(y ~ x1 + x2) lmFit Call:

Hello, I would like to suggest the following change to image.default in src\library\graphics\R\image.R: 98c98 < plot(NA, NA, xlim = xlim, ylim = ylim, type = "n", xaxs = xaxs, --- > plot(x[1], y[1], xlim = xlim, ylim = ylim, type = "n", xaxs = xaxs, This provides all the support of axis.POSIXt that plot.default gives, currently the default new plot in

Como usas la función image puedes consultar la ayuda ?image o help(image) y encontrarás el siguiente ejemplo donde se usa un diferente color Palette (mencionada por pepeceb en su respuesta). x <- 10*(1:nrow(volcano)) y <- 10*(1:ncol(volcano)) image(x, y, volcano, col = terrain.colors(100), axes = FALSE) # O puedes usar directamente el número para indicar el color image(x, y, volcano, col =

Hi all,   I have loaded the LIMMA and Biobase package and tried these commands:   library(limma) library("Biobase") data <- read.table("c:/temp/data.txt",header=T,row.names=1) ExpressionData <- as.matrix(data[,c(2,3,4,6,7,8)]) eset <- new("ExpressionSet", exprs = ExpressionData) design <- cbind(WT=1,P=c(0,1,1,0,1,1),G=c(0,1,0,0,1,0)) fit <-

Given the example: R> (levs <- quantile(volcano,c(0,0.1,0.5,0.9,0.99,1))) 0% 10% 50% 90% 99% 100% 94 100 124 170 189 195 R> levelplot(volcano,at=levs) How can I make the key categorical with the size of the divisions equally spaced in the key? E.g., five equal size rectangles with labels at levs c(100,124,170,189,195)? Apologies if this is obvious. -A R> version