similar to: Sorting the levels of a factor

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

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 <-

>>>>> "GS" == Gordon K Smyth <smyth@wehi.edu.au> >>>>> on Sat, 8 Jan 2005 01:11:30 +1100 (EST) writes: <.............> GS> p.adjust() unfortunately gives incorrect results when GS> 'p' includes NAs. The results from topTable are GS> correct. topTable() takes care to remove NAs before GS> passing

I am another person who has had trouble documenting S4 classes and (particularly) methods. The methods package itself is pretty cool by the way, but it is a pity that there are as yet no guidelines on S4 in the "Writing R Extensions" document. I have actually put together a guide on S4 documentation myself for the use of my own lab which is at

The Bioconductor core group would like to announce the 1.3 release of the Bioconductor software. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to check them out. Release 1.3 is intended to be operated with R version 1.8.X, which can be obtained at CRAN (http://cran.r-project.org/) -- WHAT FEATURES DOES THIS RELEASE PROVIDE?

The Bioconductor core group would like to announce the 1.3 release of the Bioconductor software. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to check them out. Release 1.3 is intended to be operated with R version 1.8.X, which can be obtained at CRAN (http://cran.r-project.org/) -- WHAT FEATURES DOES THIS RELEASE PROVIDE?

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 =

Hello, I have some troubles when building S4-class packages. All my (S4-)code works well (without building a package). When building a package, in the R prompt after checking S3 generic/method consistency Following error occurs: Fehler: Kann R Kode in Packet 'AddNoise' nicht laden (~Error: Can not load R code from package 'AddNoise') (and there are some warnings after the

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

Greetings! The Bioconductor core group would like to announce the 5th release of Bioconductor, version 1.4. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to upgrade existing tools and check out the new packages. Release 1.4 is intended to be operated with R version 1.9.x, which can be obtained at CRAN

Hi all. I've got a really dumb question for anyone. How do I write the output of a limma analysis (basically the topTable) to a text file? I want to output the topTable for the entire microarray (not really a topTable anymore I suppose..). Thanks for any advice! -Josh

Hi, I am trying to plot the following data so that it can be visually represented well. I tried the dotchart but I felt it was too spread out. Then I tried the barplot which is good enough for me. Is there a way to give the labels for the y-axis as in the dot chart? Also, I feel the grey level is confusing, so is there options for designs within the bars? I cannot use color as the journal wants

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

BioInformatics Scientist Job Code: 10-TR25 Location: Cambridge, MA Description We are seeking a highly motivated, independent bioinformatics scientist to join a group of scientists, analysts and programmers to develop tools and methodologies for large-scale gene expression data analysis. The group supports a variety of research projects in target and drug discovery as well as biomarker

Hello, I didn't give enough information when I sent an query before, so I'm trying again with a more detailed explanation: In this data set, each patient has a different number of measured variables (they represent tumors, so some people had 2 tumors, some had 5, etc). The problem I have is that often in later cycles for a patient, tumors that were originally measured are now missing (or

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

Dear R help, I am having a problem with the Design package and my problem is detailed here. I fit a cox model to my data and validate the Somer's Dxy using the Design package. (Because of computation time problem, i only try 10 bootstrap samples for the time being) This is the model without stratification: > library(Design) >

Hi, The problem is most likely, you need to call a R CMD BATCH with your arguments and the R-script inside of a shell script that you submit to your qsub. Unfortunately we don't use qsub anymore so can't test it, but it should be as follows: R-script eg. test.R: > ##First read in the arguments listed at the command line > args=(commandArgs(TRUE)) > > ##args is now a list of

Hi, I have two questions want to ask. 1. If I have a matrix like this, and I want to figure out the rows whose value in the 3rd column are less than 0.05. How can I do it with R. hsa-let-7a--MBTD1 0.528239197 2.41E-05 hsa-let-7a--APOBEC1 0.507869409 5.51E-05 hsa-let-7a--PAPOLA 0.470451884 0.000221774 hsa-let-7a--NF2 0.469280186 0.000231065 hsa-let-7a--SLC17A5

Hi, I am new to R and AIC scores but what I get from coxme seems wrong. The AIC score increases as p-values decrease. Since lower AIC scores mean better models and lower p-values mean stronger effects or differences then shouldn't they change in the same direction? I found this happens with the data set rats as well as my own data. Below is the output for two models constructed with the rats