Hello, I have data from a two-color, homemade, microchip array (one GPR file). The chip contains multiple probes for each gene (just to be sure I'm using the correct terms: the GPR file has multiple lines with the same NAME and readings of F635 and F532 for each gene of interest). There are also many lines marked with "EMPTY" . There is only one GPR file, and no replicates at the moment. (I'm trying to help a friend deal with an existing situation, which is less than ideal - but that's what we've got.) First, How do I deal with the multiple probes for each gene? Should I pre-process the data and calculate the mean/median for each, then feed "limma" only the aggregated values? or is there a better way (taking the variability within each group into account) ? Second, The data works fine with limma's "read.maimages()", "normalizaeWithinArrays()", and "lmFit()". However, "eBAyes" and "topTable" do not work (as explained in many other threads, they will not work without replicates). Despite the fact that it's inadvisable to continue without replicates, is there a way to perform some sort of differential expression analysis? (Akin to EdgeR's method of working when there are no replicates?) Many thanks, -gordon -- output of sessionInfo(): . -- Sent via the guest posting facility at bioconductor.org.

normalizeWithinArrays() produces an MA object. You can plot the results using plotMA(MA) The M-values are the log2-fold changes. Just select genes with large M-values. For example, o <- order(abs(MA$M),decreasing=TRUE) tab <- data.frame(MA$genes,A=MA$A,M=MA$M) tab[o[1:20],] Best wishes Gordon --------------------------------------------- Professor Gordon K Smyth, Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Vic 3052, Australia. http://www.statsci.org/smyth > Date: Tue, 26 Nov 2013 05:01:06 -0800 (PST) > From: "Gordon [guest]" <guest at="" bioconductor.org=""> > To: bioconductor at r-project.org, assafgordon at gmail.com > Subject: [BioC] Limma with homemade chip, multiple probes per gene, no > replicates? > > > Hello, > > I have data from a two-color, homemade, microchip array (one GPR file). > The chip contains multiple probes for each gene (just to be sure I'm using the correct terms: the GPR file has multiple lines with the same NAME and readings of F635 and F532 for each gene of interest). There are also many lines marked with "EMPTY" . > > There is only one GPR file, and no replicates at the moment. > > (I'm trying to help a friend deal with an existing situation, which is less than ideal - but that's what we've got.) > > First, > How do I deal with the multiple probes for each gene? > Should I pre-process the data and calculate the mean/median for each, then feed "limma" only the aggregated values? or is there a better way (taking the variability within each group into account) ? > > Second, > The data works fine with limma's "read.maimages()", "normalizaeWithinArrays()", and "lmFit()". > > However, "eBAyes" and "topTable" do not work (as explained in many other threads, they will not work without replicates). > > Despite the fact that it's inadvisable to continue without replicates, is there a way to perform some sort of differential expression analysis? > (Akin to EdgeR's method of working when there are no replicates?) > > Many thanks, > -gordon ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}