Hi, I have already analyzed some gene expression data using RMAExpress, writing to a tab-delimited file and then using the SAM plugin for MS Excel. I had great results and didn't have to use R at all. Now I would like to repeat the process using R. I don't really understand how to work with eSets or ExpressionSets, which is what the affy package stores expression data in; and I don't think the samr package even uses these objects... Anyways, here is the workflow I am trying to do in R: * Read .CDF file for RAE230A, * Read .CEL files for 12 RAE230A Genechips * Compute RMA expression measures using background adjustment and quantile normalization (default median polish for summarization) * Log 2 transform the expression measures ....repeat for 12 RAE230B Genechips * Join the data from RAE230A and RAE230B into one table; probesets with identical names will have ##rae230a or ##rae230b appended to their name or some other method can be used to differentiate probesets with identical names between the two chips. * Label the the samples according to three experimental groups, (i.e. "1","2","3") * Use SAM with samr to create a list of genes with pFDR ~ 5% How much of a headache would it be to do this in R? Is there a quick way to convert an Expression Set to a format usable by samr? Has anyone else used the same combination (affy and samr)? Thanks in advance. -R [[alternative HTML version deleted]]

The SAM implementation in the R package siggenes (which will usually lead to slightly different results than the implementation in samr) can handle ExpressionSet objects. However, just one ExpressionSet object so that you either need to preprocess all cel-files at once or use the exprs function do extract the expression values from your ExpressionSet objects, cbind the resulting matrices, and use the combined matrix. Holger -------- Original-Nachricht -------- > Datum: Mon, 30 May 2011 00:34:32 -0400 > Von: Richard Student <richard.a.student at="" gmail.com=""> > An: bioconductor at r-project.org > Betreff: [BioC] RMA (affy) followed by SAM (samr) > Hi, > > I have already analyzed some gene expression data using RMAExpress, > writing > to a tab-delimited file and then using the SAM plugin for MS Excel. I had > great results and didn't have to use R at all. Now I would like to repeat > the process using R. > > I don't really understand how to work with eSets or ExpressionSets, which > is > what the affy package stores expression data in; and I don't think the > samr > package even uses these objects... > > Anyways, here is the workflow I am trying to do in R: > > * Read .CDF file for RAE230A, > * Read .CEL files for 12 RAE230A Genechips > * Compute RMA expression measures using background adjustment and quantile > normalization (default median polish for summarization) > * Log 2 transform the expression measures > > ....repeat for 12 RAE230B Genechips > > * Join the data from RAE230A and RAE230B into one table; probesets with > identical names will have ##rae230a or ##rae230b appended to their name or > some other method can be used to differentiate probesets with identical > names between the two chips. > > * Label the the samples according to three experimental groups, (i.e. > "1","2","3") > > * Use SAM with samr to create a list of genes with pFDR ~ 5% > > How much of a headache would it be to do this in R? Is there a quick way > to > convert an Expression Set to a format usable by samr? Has anyone else > used > the same combination (affy and samr)? > > Thanks in advance. > -R > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor --