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You asked the same question on the Bioconductor mailing list back in August. At that time, you suggested yourself a solution for how the adjusted p-values should be interpreted. I answered your query and told you that your interpretation was correct. So I'm not sure what more can be said, except that you should read the article Wright (1992), which is cited in the help entry for p.adjust(),

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

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

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 --

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

Is it possible to vectorize anova over the output of a vectorized lm? I have a gene expression matrix with each row being a gene and columns for samples. There are several factors with interactions. I can get p values by looping over the matrix with lm and anova, but I would like to make this as computationally efficient as possible. I am able to vectorize the lm command, but when I try to use

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

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 =

R-devel, I'm interested in looking at some examples of existing R packages that rely heavily on S4 classes to get a feel for varying styles and package organization techniques. Could you recommend any packages that might serve as a good starting point? Thanks in advance, Jeff

R-devel, I'm interested in looking at some examples of existing R packages that rely heavily on S4 classes to get a feel for varying styles and package organization techniques. Could you recommend any packages that might serve as a good starting point? Thanks in advance, Jeff

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")

I was trying to plot some data in R. I used the following code to draw a loess fit and got the output as >?lines(lowess(log(abs(t(res))), log(abs(t(synthesised)))), col="red") Error in lowess(log(abs(t(res))), log(abs(t(synthesised)))) :?? NA/NaN/Inf in foreign function call (arg 1) Then I thought to use your Limma package for background correction. Do you think it's a right

Hi Hilmar, weird. The memory problem seems be due to recursion (my R, version 3.3.3, says: Error: evaluation nested too deeply: infinite recursion / options(expressions=)?, just write traceback() to see how it happens), but why does it segfault with xlsx? Nb xlsx is the culprit: neither rJava nor xlsxjars cause the problem. On the other hand, quick googling for r+xlsx+segfault returns tons of

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

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

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

Dear All, How to cite the PDF user's guide for the LIMMA package? This is not about how to cite the LIMMA package. Roger Roger L. Vallejo, Ph.D. Computational Biologist & Geneticist U.S. Department of Agriculture, ARS National Center for Cool & Cold Water Aquaculture 11861 Leetown Road Kearneysville, WV 25430 Voice: (304) 724-8340 Ext. 2141 Email: roger.vallejo@ars.usda.gov

Hi again, I have been playing around with the order of loading packages, and as far as I can tell, there's nothing specific with affycoretools that's causing my Rgui to crash (i.e., shuts down and the Microsoft 'please send error report' box pops up). Instead, it has something to do with the order & type of packages that are loaded that add items to the menu bar by

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