similar to: R package to analyze time course microarray data

Analysis of Microarray Data Using S-PLUS, R and S+ArrayAnalyzer 23rd March 2006 Presenter: Adam Diaz Venue: Insightful UK, Network House, Basing View, Basingstoke, Hants RG21 4HG This is the last chance to register for this unique course being run by a member of Insightful's microarray development team from the US. Extract Microarray technology is complex, and experiments using

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

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

hi all i started recently using R and i found myself stuck when i try to analyze microarray data. i use the "affy" package to obtain the intensities of the probes, i have two CTRs and two treated. HG.U133A.Experiment1.CEL HG.U133A.Experiment2.CEL HG.U133A_Control1.CEL HG.U133A_Control2.CEL 1007_s_at 2156.23115 467.75615 364.60615 362.11865

[BioC] ANN: Introductory R and Bioconductor Mini Course , Seattle, April 12-14 We will present a short course on using Bioconductor, primarily aimed at analyzing microarray data, over 2 1/2 days in April. The course will be a mix of lectures and practical labs. Instructors: Robert Gentleman, Seth Falcon, Martin Morgan, and Nolwenn Le Meur Topics: Introduction to R Preprocessing of

Hi, May be this helps: ?set.seed(24) ?mydata4<- as.data.frame(matrix(sample(1:100,10*38,replace=TRUE),ncol=38)) ?dim(mydata4) #[1] 10 38 ?library(matrixStats) res<-do.call(cbind,lapply(1:400, function(i) {permutation<-sample(mydata4); (rowMeans(permutation[,1:27])-rowMeans(permutation[,28:38]))/(rowSds(permutation[,1:27])+rowSds(permutation[,28:38]))} )) ?dim(res) #[1]? 10 400 A.K.

Hey So sorry to be a total newbie, but i'm just finding my feet with R. I heard on the grapevine i could recreate a scanned microarray image, or at least get a good graphic of it from a just a data file. I have .txt files for illumina beadarrays but no images cos the service we used didn't send them. The 'beadarray' package seems to require TIFFs to get the graphic output. Does

Dear Listers: Currently I am doing a research using a microarray data. I have two questions and hope I can get some help from here: 1. I have a dataset like the following, in which V1 is geneid, v3...are the fold changes of expression levels for different patients. There are multiple probes for one gene, so there are multiple rows. You can see from column V11 and V13, the fold changes are very

Hi, I am following the protocol outlined here for analysis of single channel Agilent microarray data: http://matticklab.com/index.php?title=Single_channel_analysis_of_Agilent_microarray_data_with_Limma I keep getting the following error message when using Limma's read.maimages function to load my data into an RGList object: Error in RG[[a]][, i] <- obj[, columns[[a]]] : number of

We are pleased to announce version 0.8 of the acs package for R, now available on CRAN (<http://cran.r-project.org/web/packages/acs/index.html>. The package provides a general toolkit for managing, analyzing, and presenting data from the U.S. Census American Community Survey (ACS). Confidence intervals provided with the data are converted to standard errors and bundled with estimates in

We are pleased to announce version 0.8 of the acs package for R, now available on CRAN (<http://cran.r-project.org/web/packages/acs/index.html>. The package provides a general toolkit for managing, analyzing, and presenting data from the U.S. Census American Community Survey (ACS). Confidence intervals provided with the data are converted to standard errors and bundled with estimates in

Dear R-users: I am using the package MAANOVA to analyze microarray data and have encountered problems when trying to get interactions. I am a newbie in both, R and maanova, and I do not have good knowledge in statistical methods. I have four effects: Effects Levels Var 2 Ind 2 Trat 2 Time 4 Sample 3 <-- biological replicate Spot 4 <-- technical replicate I had

Is there any package that allow you to perform "MA plot" like graph for Toray microarray data? Unlike Affymetrix CEL file which contain 2 values (R and G), Torray raw data only contain 1 value. MA-plot is Affymetrix specific which usually available for in (limma) package. P. Dubois [[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

For any given pre-specified gene or short list of genes, yes the Cox model works fine. Two important caveats: 1. Remeber the rule of thumb for a Cox model of 20 events per variable (not n=20). Many microarray studies will have very marginal sample size. 2. If you are looking at many genes then a completely different strategy is required. There is a large and growing literature; I like Newton

Hi all.. I'm very new R, and i'm analyzing microarray data using Bioconductor.. Recently i was given microarray data to analyze. The problem is whenever i run MAS5 presence calls algorithm, it throws an error saying NA/NaN/Inf in foreign function. How do i remove such NA/NaN/Inf's ?? I tried na.omit(dataframe) but stil problem exists. dimension of matrix (data) is 35556 7. >

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Hi: I have clustered microarray gene expression data and trying to map between microarray probe, gene, pathway, gene ontology, and homology for a set of (affy) microarray probes. Is there any package in R which facilitates this? I am looking at bioconductor, but till now could not find a solution. A link to some worked example would be appreciated. Thanks and regards. John [[alternative HTML

Could someone kindly help me with the following question: when I analyze microarray data I need to fit multiple linear regression models between genes and clinical patameters followed by estimation of the p-values. What's the solution to implement Westfall and Young's algorithm + resampling into the scheme: lm -> stepAIC -> anova. Actually permcor works fine for me in the case of

Hi I am Aadhithya I am trying to write a code to classify microarray data (AML and ALL) using SVM in R my code goes like this : library(e1071) train<-read.table("Z:/Documents/train.txt",header=T); test<-read.table("Z:/Documents/test.txt",header=T); cl <- c(c(rep("ALL",10), rep("AML",10))); model<- svm(train,cl); pred <-