similar to: subsetting the gene list

Dear R-Help, I am using the function "topTable" from the LIMMA package. To estimate adjusted P-values there are several options (adjust="fdr" , adjust="BH") as shown below: topTable(fit, number = 10, adjust = "BH", fit$Name) I guess any of these options (fdr, BH, etc.) is using a default of FDR=0.05 which is quite conservative (i.e., very

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

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

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, 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 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 am not only interested in finding out which genes are the most highly up- or down-regulated (which I have done using the linear models and Bayesian statistics in Limma), but I also want to know which genes are consistently highly transcribed (ie. they have a high intensity in the channel of interest eg. Cy5 or Cy3 across the set of experiments). I might have missed a straight forward

Hi, I need some help with the interpretation of B statistics generated by eBayes in the limma package. I want to compare gene expression in three groups of Affy samples. The expression set has been imported from GeneSpring using GSload.expBC and a linear model fitted to the data using a design based on the three groups (6, 5, and 5 samples in each group, respectively). I have then made 3

Dear Sirs, I am a new user of the R package. When I try to use the curve function it confuses me. > curve(x^2) Works fine. > curve(x) Makes a complaint I don't understand. Why is x^2 valid and x is not? I check the documentation of curve, and it says the first argument must be an expression containing x. > expression(x) Is an expression containing x. > curve(expression(x))

Dear Sirs, I am exploring the R package and its documentation. I find there is the function example which runs examples from documentation pages. What confuses me is that running example interferes with the variables I have in my workspace. > x <- 0 > example(mean) > x Now x is a vector of some values coming from the example. Am I using example in the wrong way? In situation like

Hi list, I am fitting microarray data (intensity) model using the lme package in R environment. I have 5 fixed variables in the model. One of the fixed variables is genes. I am trying to get p-values for different genes. But I am getting only one p-value for all genes together. I can get a list of p-value when I run lm. Why can't this work in lme? My aim is to do multiple comaprison of all

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 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

I would like to load ApoAI.RData. During the operation of reading this data an error occurs. There is also a problem with STF file. > library (limma) > load("ApoAI.RData") Warning message: 'RG' looks like a pre-2.4.0 S4 object: please recreate it > objects() [1] "RG" > names(RG) [1] "R" "G" "Rb"

I have a very basic question about limma. Assume I have experiments from 3 or more RNA sources in a reference design. It is easy to define individual contrasts but I want to specify a contrast matrix that tests for significant differences among ALL the different RNA sources (i.e. the analogous thing to a simple One-Way ANOVA). How can I do that? Thanks! Max --

Hi, all, I am new to R or even to statistics. Not sure if the question has a answer. But I couldn't find a straight forward answer in the help mailing list. I need use MicroArray data to select several diagnostic genes between Normal samples and Tumor samples and use these genes to predict unknow samples. Since the sample size is so small and data doesn't follow normal distribution, I am

Can someone show me some code to do normalization by the median of some control genes for the example below? Many Many Thanks in advance This strategy selects a subset of genes (called ?control genes?) and makes the median of their data distribution similar across arrays. ??? ??? id1??? id2??? id3 control1??? 0.8??? 0.7??? 0.6 control2??? 0.6??? 0.2??? 0.4 probe1??? ??? 0.3??? 0.2??? 0.5

Hi, this is a problem that occurs in the presence of two libraries (limma, xlsx) and leads to a crash of R. The problematic code is the wrong application of sweep or the product ("*") function on an LIMMA MAList object. To my knowledge, limma does not define a "*" method for MAList objects. If only LIMMA is loaded but not package xlsx, the code does not crash but rather

Dear Hilmar Perhaps this gives an indication of why the infinite recursion happens: ## after calling `*` on ma and a matrix: > showMethods(classes=class(ma), includeDefs=TRUE, inherited = TRUE) Function: * (package base) e1="FOOCLASS", e2="matrix" (inherited from: e1="vector", e2="structure") (definition from function "Ops")

Dear all, I have a question about limmaGUI that is usually run in R environment. My problem is loading data into the programm. I have 6 gpr files that apparently are not compatible with limma. Everytime I'm trying to load the data (including a RNA targets file, an error appears:Error reading files. that I'm not sure,but seems to have something to do with the format of my files