similar to: File format for single channel analysis of Agilent microarray data in Limma?

I have a presence/absence matrix for which I create a distance matrix and then perform pco analysis on. /library(ecodist) table <- read.table("matrix.pa") dist <- dist(table, method = "euclidean", diag = FALSE, upper = FALSE) dist.pco <- pco(dist)/ When I plot the pco analysis of the distance matrix I want to be able to distinguish between certain characters, for

Hi Everyone, I have been trying to read some Arrayvision files( 2 channel cDNA) and am having some problem. My code is : setwd('C:/work/data/limma/ndd1'); files <- c('ndd1_1.txt','ndd1_2.txt','ndd1_3.txt'); RG=read.maimages(files,"arrayvision",sep="\t"); #Normalisation MA=normalizeWithinArrays(RG); #plotPrintTipLoess(MA); #Fit Linear

Hello! I have created a bplot-figure using this code: *file <- "2dcali_red.ttt" ux<-as.matrix(read.table(file, dec = ",")) mode(ux)<-'numeric' vel<-ux[,1] ang<-ux[,2] x<-ux[,3] y<-ux[,4] dat<- data.frame(ang=ang, x=x,y=y) require(rms) ddist2 <- datadist(dat) options(datadist="ddist2") fitn <- lrm(ang ~ rcs(x,4) +

Hi I would like to plot the variation of some mean values with time, and have the standard deviation around the mean shaded on the plot. I could not find a way to have the shaded area on the curve with the default R commands, do I need a special package to do that? Or any idea of a way with the default R commands? Many thanks Thomas -- Thomas Loridan King's College email: thomas.loridan

Hello, I''m using Xen-unstable and the kernel 2.6.18. Doing some particular tests, I need to disable the SMP Support in the kernel configuration and surprisingly I receive this error after compiling the kernel: CC init/version.o LD init/built-in.o LD .tmp_vmlinux1 drivers/built-in.o: In function `take_machine_down'': machine_reboot.c:(.text+0x58a6c):

Hi, I would like to analyze some agilent aCGH copy number files. As a start, I would like to normalize this data. I don't know what is the standard way to do this. Which package is the standard one that people use for this purpose? The chips that I am looking at are the agilent sure print 1M (G4447a) array and a custom chip with similar format. My raw data is a text file with spot locations

Hey guys, Can anyone help? I did a correspondance analysis and made a plot. I also have a specific list of nodes that i want to find in my plot and want to either color the nodes that appear in my list differently, or put some kind of border around that group of nodes... Would anyone know how to do this? Also, would this post be more relevant here or in the bioconductor forum? -- View this

Dear Sirs, How can I revert to an older limma version? Typing "install.packages("limma")" in R gives a list of mirrors. How can I install the version I want after I obtain and untar the file (e.g, limma_2.9.1.tar.gz)? I am running R 2.5.0 on a Linux machine (CentOS 5). When using limma it will not go past the read.maimages command. I get this error: Error in

Dear mailing group, This is my first time here. Glad to have this resource! I am currently trying to load an Excel file into R (limma package loaded) using the source(*name of directory*) command, but it cannot open the file. I renamed the file as .R and .RData, to no avail. The Excel data contains one gene name per row and about 100 data points per gene (columns). I am only used to

Hi fn <- dir(pattern="txt",full.name=T) > fn [1] "./GSM696980_US81503234_252741110209_S01_CGH_107_Sep09_1_1_32914.txt" [2] "./GSM696981_US81503234_252741110209_S01_CGH_107_Sep09_1_2_32916.txt" [3] "./GSM696982_US81503234_252741110209_S01_CGH_107_Sep09_1_3_33021.txt" [4] "./GSM696983_US81503234_252741110209_S01_CGH_107_Sep09_1_4_33024.txt"

Hi, I have a question about filterMicroRna in AgiMicroRna package function for filtering probes in Agilent microRNA dataset. >ddPROC = filterMicroRna(ddNORM.micro, dd, control = TRUE, IsGeneDetected = TRUE, wellaboveNEG = FALSE, limIsGeneDetected = 75, limNEG = 25, makePLOT = TRUE, target.micro, verbose = TRUE) If in a dataset there are two or more sample replicates and in the step of

Dear list members, I am analysing my microarray data using limma package. Now I encounter several problems. Looking forward to your suggestions! Question 1: During the process of background correction using method="normexp", four warning messages appeared as "NaNs produced in: log(x)" (as you can see in the program posted below). What does that mean? How will it effect the

Dear R help, In limma package, contrasts.fit() function is very useful. I am wondering whether there is a similar function for lme object, which means given a mixed linear model fit, compute estimated coefficients and standard errors for a given set of contrasts. Thanks, Shirley

Hello All, I am new to R and want to use R to scale my data before analysis. I need to do two fold scaling: a). scale on a per object (chip) basis, scale to a mean of 0 and stddev to 1; b). scale on a per feature basis: scale data linearly to the interval [0,1]. Could somebody help me with this? Thanks a lot, Jas __________________________________

Hello! Just want to get some suggestions on which R package is good for analyzing time course microarray data. Thank you so much for your input! Sincerely, Allen [[alternative HTML version deleted]]

Dear all, i have microarray data of 3 classes of patients. It's not a time course experiment only steady state. I used a rule-based method to classify the groups by the expression of the genes. This works out so far. Nevertheless I want to check my results with an other method. Therefore I look for one and want to ask you, what you suggest. I have 3 different patient groups, only the steady

Full_Name: Eric Libby Version: 2.1.1 OS: OS Tiger Submission from: (NULL) (65.93.158.117) I am trying to analyze microarray data of 42 human arrays. I typed in the following instructions: library(affy) Data <-ReadAffy() eset <- expresso(Data, normalize.method="invariantset", bg.correct=FALSE, pmcorrect.method="pmonly",summary.method="liwong") And I get some

3rd Millennium is announcing the release of its award winning Array Repository and Data Analysis System (ARDAS) version 2. ARDAS is a web-enabled enterprise software system that provides a complete and fully integrated solution to microarray data acquisition, management, and analysis. ARDAS includes three main modules: 1- A Laboratory Information Management System (LIMS) 2- A repository and data

Hi, concerning my earlier mail, maybe someone has noted from the variable names that I try to analyse mircoarrary experiments. Does anybody know of a R-implementation of the two-step mixed-model normalization procedure proposed by Wolfinger et al. (2001) J. Comput. Biol. 8:625-637? That would be great, best, joerg

Prof. Javier Cabrera will be giving the online course "DNA Microarray Data Analysis" from Jan. 28 - Feb. 25 at statistics.com. Dr. Cabrera is co-author of "Exploration and Analysis of DNA Microarray and Protein Array Data" (the course text; Wiley) and has published a number of articles on gene expression data analysis, data mining and multivariate methods in leading