Hi Jim, I'm learning to use your limma2annaffy function, and I have a few questions. In the affycoretools vignette (Feb 6, 2007), you call limma2annaffy this way: > limma2annaffy(eset, fit2, design, annotation(eset), pfilt = 0.05) I think there's a typo in this, because you've left out the contrast matrix. When I try the same on my data: > limma2annaffy(gcrma.pres, fit2, design, annotation(gcrma.pres),pfilt=0.05) Error in vector("list", dim(contrast)[2]) : negative length vectors are not allowed When I try naming the annotation(gcrma.pres) argument, I get this: > limma2annaffy(gcrma.pres, fit2, design, lib=annotation(gcrma.pres),pfilt=0.05) Error in vector("list", dim(contrast)[2]) : argument "contrast" is missing, with no default It does work when I add the contrast matrix: > limma2annaffy(gcrma.pres, fit2, design, cont.matrix,annotation(gcrma.pres),pfilt=0.05) So, besides pointing out an apparent error in the vignette, I had a question as to what you would do if you didn't use a contrast matrix? Now, most all the time that I analyze affy data I do use a contrast matrix, but you don't always have to use one. I have some other questions/suggestions to improve the ease of use of affycoretools, but they are too complicated to put in this e-mail... Thanks, Jenny > sessionInfo() R version 2.5.0 Under development (unstable) (2007-02-03 r40636) i386-pc-mingw32 locale: LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 attached base packages: [1] "splines" "tools" "stats" "graphics" "grDevices" "utils" [7] "datasets" "methods" "base" other attached packages: canine2 affyQCReport lattice geneplotter RColorBrewer "1.15.13" "1.13.16" "0.14-16" "1.12.0" "0.2-3" simpleaffy made4 scatterplot3d ade4 affyPLM "2.9.1" "1.8.0" "0.3-24" "1.4-2" "1.11.13" affydata affycoretools annaffy xtable gcrma "1.11.1" "1.7.7" "1.7.2" "1.4-3" "2.7.1" matchprobes biomaRt RCurl XML GOstats "1.7.4" "1.9.16" "0.8-0" "1.4-1" "2.1.11" Category genefilter survival KEGG RBGL "2.1.11" "1.13.8" "2.31" "1.15.1" "1.11.4" annotate GO graph limma affy "1.13.6" "1.15.1" "1.13.5" "2.9.10" "1.13.14" affyio Biobase RWinEdt "1.3.3" "1.13.36" "1.7-5" > Jenny Drnevich, Ph.D. Functional Genomics Bioinformatics Specialist W.M. Keck Center for Comparative and Functional Genomics Roy J. Carver Biotechnology Center University of Illinois, Urbana-Champaign 330 ERML 1201 W. Gregory Dr. Urbana, IL 61801 USA ph: 217-244-7355 fax: 217-265-5066 e-mail: drnevich at uiuc.edu

Hi Jenny, Jenny Drnevich wrote: > Hi Jim, > > I'm learning to use your limma2annaffy function, and I have a few > questions. In the affycoretools vignette (Feb 6, 2007), you call > limma2annaffy this way: > > > limma2annaffy(eset, fit2, design, annotation(eset), pfilt = 0.05) > > I think there's a typo in this, because you've left out the contrast > matrix. When I try the same on my data: Yeah, that's a typo. It never came up in a build/check cycle because it never really gets called in the Sweave() document. Thanks for pointing it out though. > > > limma2annaffy(gcrma.pres, fit2, design, annotation(gcrma.pres),pfilt=0.05) > Error in vector("list", dim(contrast)[2]) : > negative length vectors are not allowed > > When I try naming the annotation(gcrma.pres) argument, I get this: > > > limma2annaffy(gcrma.pres, fit2, design, > lib=annotation(gcrma.pres),pfilt=0.05) > Error in vector("list", dim(contrast)[2]) : > argument "contrast" is missing, with no default > > It does work when I add the contrast matrix: > > > limma2annaffy(gcrma.pres, fit2, design, > cont.matrix,annotation(gcrma.pres),pfilt=0.05) > > > So, besides pointing out an apparent error in the vignette, I had a > question as to what you would do if you didn't use a contrast matrix? Now, > most all the time that I analyze affy data I do use a contrast matrix, but > you don't always have to use one. I have some other questions/suggestions > to improve the ease of use of affycoretools, but they are too complicated > to put in this e-mail... You can _always_ use a contrasts matrix, even if you don't need one. The thing about limma2annaffy() is I use the colnames of the contrasts matrix to name the output files, so there has to be one. So there are two things you can do. Say you fit a factor effects model with a set of tumor/normal samples, three of each: > design <- model.matrix(~ factor(rep(1:2, each=3))) > design (Intercept) factor(rep(1:2, each = 3))2 1 1 0 2 1 0 3 1 0 4 1 1 5 1 1 6 1 1 attr(,"assign") [1] 0 1 attr(,"contrasts") attr(,"contrasts")$`factor(rep(1:2, each = 3))` [1] "contr.treatment" Now the second column of the design matrix specifies the tumor - normal contrast, so a contrasts matrix is superfluous. However, this contrast will work with limma2annaffy(): > contrast <- matrix(c(0,1), dimnames=list(c("normal", "tumor"), "tumor vs normal")) > contrast tumor vs normal normal 0 tumor 1 Or you can just specify a cell means model in the first place. Alternatively, you could just select the probesets that are significant and use probes2table(). But that would be more work if you want t-stats, p-values, etc. If you want to send me an email offline, I would be happy to hear your suggestions. I am always up for improving things. Best, Jim -- James W. MacDonald University of Michigan Affymetrix and cDNA Microarray Core 1500 E Medical Center Drive Ann Arbor MI 48109 734-647-5623 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues.