similar to: Newbie: Where is lmFit function?

Hi, I have two data set of normalized Affymetrix CEL files, wild type vs Control type.(each set have further three replicates). > wild.fish AffyBatch object size of arrays=712x712 features (10 kb) cdf=Zebrafish (15617 affyids) number of samples=3 number of genes=15617 annotation=zebrafish notes= > Dicer.fish AffyBatch object size of arrays=712x712 features (10 kb) cdf=Zebrafish (15617

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 <-

Hallo, > fit12<-lmFit(qrg[,1:2]) > t12<-toptable(fit12,adjust="fdr",number=25,genelist=qrg$genes[,1]) > t12 ID logFC t P.Value adj.P.Val B 522 PLAU_OP -6.836144 -8.420414 5.589416e-05 0.01212520 2.054965 1555 CD44_WIZ -6.569622 -8.227938 6.510169e-05 0.01212520 1.944046 Can anyone tell me what the difference is between P.Value

Dear BioConductor and R fellow users I apologize in advance for double posting, but I am not sure which list would actually be best fit for this message. I am experiencing a weird error with my R installation on Ubuntu 10.04.4 (LTS) 64bit: When I run R on the terminal everything goes smoothly: $R R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation

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 <-

Hi, I am a Ph.D. student from Québec, Canada. I’m a beginner with R and Bioconductor. Until now the only experience I have is in analyzing microarray data using affy and limma packages. Now I am trying to analyze Rat Gene 10 st arrays and I would like to run RMA analysis and Smyth moderated t test on those arrays. Since no cdf official package is available for those arrays, after reading many

Hi, I have a question concerning the analysis of some affymetrix chips. I downloaded some of the data from GEO GSE11324 (see below). In doing so I'm stuck after I identified the probesets with significant changes. I have problems in assigning probeset specific gene names as well as getting the genomic coordinates. Furthermore I have no clue how to deal with the fact, that most genes have

Hi all, My name is Amy, I am a masters student in Bioinformatics at North Carolina State University. I am working on a project and I am trying to use the lumi R package for microarray data analysis. I have shown the sample code here and have questions about modifying the sample code for my own data. lumi package in R, example.lumi, the sample data has 8000 features and 4 samples I have

Dear R users, I'am using marray and Limma packages to analyze genepix output. 1) how can I filter bad spots from my data (data contains 3 types of bad spots). my experiment contains 12 samples and the bad spot are not associated to the same probes 2) how can I remove control probes from my data ? I'm sorry, i'm new with R and I can't find answer in packages doc. best regards,

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

Hi, I am relatively new to R and Bioconductor and am trying to filter the topTable that I generated of differentially expressed genes from my normlized eset file comprised of ~ 40 HG-133A Affy microarrays . I would like to see if particular probesets are represented in this list. Alternatively I would like to generate a topTable of differentially expressed genes using only specified probesets

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

Hi, I am supposed to use exprs as a function. Where can i download exprs function? I tried searching at bioconductor and seach engine but no luck. Is it located in one of the library in R? thanks. C -- View this message in context: http://www.nabble.com/exprs-function-download-tp15654560p15654560.html Sent from the R help mailing list archive at Nabble.com.

On Wed, December 22, 2004 12:11 am, r.ghezzo at staff.mcgill.ca said: > ----- Forwarded message from r.ghezzo at staff.mcgill.ca ----- > Date: Mon, 20 Dec 2004 15:45:11 -0500 > From: r.ghezzo at staff.mcgill.ca > Reply-To: r.ghezzo at staff.mcgill.ca > Subject: [R] problems with limma > To: r-help at stat.math.ethz.ch > > I try to send this message To Gordon

Hola, buenas tardes, Hace unos dias que intento cargar unos datos de microarrays del ncbi con versión de R 2.15.2 de 32 bits en windows xp. he utilizado el siguiente codigo: library(Biobase) library(GEOquery) library(limma) gset <- getGEO("GSE6536", GSEMatrix =TRUE) Al hacerlo me da este error: "Error in function (type, msg, asError = TRUE) : couldn't connect to

Hello, I am to run this R script but i keep getting this error. > expr<-exprs(golubMerge) Warning message: The exprSet class is deprecated, use ExpressionSet instead I tried to find information on the website but no luck. (exprSet...etc) thank you. -- View this message in context: http://www.nabble.com/expression-matrix-tp15912874p15912874.html Sent from the R help mailing list archive

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

Neither biocLite nor the GUI menus can install packages on my system. Here is relevant output: > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 11.1 year 2010 month 05 day 31 svn rev 52157 language R version.string R version 2.11.1 (2010-05-31) > source("http://bioconductor.org/biocLite.R") BioC_mirror =

I've asked a question in the BioConductor list about package management. My solution depends on your answer to the following question. Are installed R packages "relocatable"? I mean relocatable in the same sense that files in a RedHat RPM file might be "relocatable" after compiling (http://www.rpm.org/max-rpm/ch-rpm-reloc.html). This allows one to build a package as the

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