Hi Maxim, This is the wrong list for this question, please subscribe to and ask this question on the bioconductor list.
Info on how to subscribe is here: http://www.bioconductor.org/docs/mailList.html -steve On Mon, Mar 29, 2010 at 4:24 PM, Maxim <deeeperso...@googlemail.com> wrote: > 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 different probesets with differential transcriptional > outcomes. > > > I did this based on the affy and limma manuals like: > > targets file: > Name FileName Target > 0h1 GSM286031.CEL control > 0h2 GSM286032.CEL control > 0h3 GSM286033.CEL control > 3h1 GSM286034.CEL three > 3h2 GSM286035.CEL three > 3h3 GSM286036.CEL three > 6h1 GSM286037.CEL six > 6h2 GSM286038.CEL six > 6h3 GSM286039.CEL six > > > library(affy) > library(limma) > library(vsn) > > pd <- read.AnnotatedDataFrame("er_for_affy.txt", header = TRUE, row.names = > 2) > pData(pd) > #### load > a <- ReadAffy(filenames = rownames(pData(pd)), phenoData = pd, verbose = > TRUE) > #### normalize > x <- expresso(a, bg.correct = FALSE, normalize.method = "vsn", > normalize.param > = list(subsample = 1000), pmcorrect.method = "pmonly", summary.method = > "medianpolish") > ### genes with highest variation > library(hgu133plus2.db) > rsd <- apply(exprs(x), 1, sd) > sel <- order(rsd, decreasing = TRUE)[1:250] > > > u<-mget(row.names(exprs(x)[sel,]),hgu133plus2SYMBOL) > heatmap(exprs(x)[sel, ], labRow=u) > ### in this case it works to extract the gene symbol > > > ### limma contrasts > design <- model.matrix(~ -1+factor(c(1,1,1,2,2,2,3,3,3))) > colnames(design) <- c("control", "three", "six") > fit <- lmFit(x, design) > meanSdPlot(x) > contrast.matrix <- makeContrasts(three-control, six-control, levels=design) > fit2 <- contrasts.fit(fit, contrast.matrix) > fit2 <- eBayes(fit2) > #### top list > topTable(fit2, coef=1, adjust="BH", number=20, sort.by="M") > library(hgu133plus2.db) > u<-mget(row.names(fit2),hgu133plus2SYMBOL) > > How can I produce a topTable result with according gene names, somehow I do > not understand the genelist argument? > > Next, I would like to produce a standard clustering of the "fold changes" > observed within (averaged) contrasts 1 (three - control) and 2 (six - > control) and a heatmap presentation of the results. How to extract for > example all fold-changes of those genes with a p-value<0.001 in at least one > of the two contrasts? > > The coordinates of the genes I seem to get with > v<-mget(row.names(fit2),hgu133plus2CHRLOC) > v<-mget(row.names(fit2),hgu133plus2CHRLOCEND) > But again I do not know, how to implement it into my fit2 object or topTable > results. Furthermore there are many probesets with multiple mappings, should > these not be excluded from the analysis? > > Actually, in the end I'd like to get the corresponding genes' coordinates in > a way, that the maximum region size is given, eg in case of genes with > multiple TSSs. > > As mentioned above, I do not know how to deal with the fact, that many genes > are represented with mutliple probesets, often with different fold changes - > is there a general recipe to deal with this question? Furthermore there are > many probesets with multiple mappings, should these not be excluded from the > analysis? > > I know it's a lot of questions, so is there a general source of information, > that may help me to overcome the hurdles? > > Maxim > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Steve Lianoglou Graduate Student: Computational Systems Biology | Memorial Sloan-Kettering Cancer Center | Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
