Dear Matthew, Thanks for your reply. I know there's a general purpose library hgu133plus2frmavecs that was produced using microarray data from diverse tissues and batches. However, I am interested in a specific tissue only and so don't need to consider probes that may not be reliable in it. So I want to know if I need my own version of normalisation parameters based solely on data from tissue of interest or I can simply rely on general purpose library at any rate. I've already processed the data using the general purpose library. And now it's the turn to develop my own version of normalisation parameters myself and I came across the error. In fact, I tried the procedure with artificially designated two batches. Interestingly, it also produced an error indicating that the batches were not of the same size (I split the sample into two batches of sizes 71 and 70, respectively). Any suggestion? Regards, TH 2013³â 5¿ù 31ÀÏ ±Ý¿äÀÏ¿¡ Matthew McCall<mccallm@gmail.com>´ÔÀÌ ÀÛ¼º: > The issue is that you are trying to estimate between-batch residual > variances with only 1 batch: > abatch.ref <- makeVectorsAffyBatch(files.ref, > rep(1,length(files.ref)), file.dir=FILED) > > I'm curious why you are making your own fRMA vectors. HGU133plus2 has > pre-made frozen parameter vectors in the hgu133plus2frmavecs package, > so you could use those to preprocess your data. > > Best, > Matt > > On Fri, May 31, 2013 at 2:40 AM, Tae-Hoon Chung <hoontaechung@gmail.com> wrote: >> Hi, all; >> >> I encountered the following error while using makeVectorsAffyBatch() >> function in frmaTools library on 141 Affymetrix HG-U133 Plus 2 chips >> (single batch). >> >> >> abatch.ref <- makeVectorsAffyBatch(files.ref, rep(1,length(files.ref)), >> file.dir=FILED) >> 1 reading GSM493958.CEL ...instantiating an AffyBatch (intensity a >> 1354896x141 matrix)...done. >> Reading in : GSM493958.CEL >> Reading in : GSM493960.CEL >> Reading in : GSM493965.CEL >> Reading in : GSM493966.CEL >> Reading in : GSM493970.CEL >> >> ¡¦ >> >> Reading in : GSM494235.CEL >> Reading in : GSM494237.CEL >> Reading in : GSM494240.CEL >> Data loaded >> >> Background Corrected >> >> Normalized >> >> Beginning Probe Effect Calculation ... >> >> Finished probeset: 1000 >> >> Finished probeset: 2000 >> >> Finished probeset: 3000 >> >> Finished probeset: 4000 >> >> ¡¦ >> >> Finished probeset: 53000 >> >> Finished probeset: 54000 >> >> Probe Effects Calculated >> >> Probe Variances Calculated >> >> Probe Set SDs Calculated >> >> Beginning Median SE Calculation ... >> >> Error in if (any(w < 0)) { : missing value where TRUE/FALSE needed >> >> >> Any suggestion? >> I ran the code under following environment: >> >> >>> sessionInfo() >> R version 2.15.2 (2012-10-26) >> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) >> >> locale: >> [1] C >> >> attached base packages: >> [1] stats graphics grDevices utils datasets methods base >> >> other attached packages: >> [1] hgu133plus2cdf_2.11.0 AnnotationDbi_1.20.7 frmaTools_1.10.0 >> [4] frma_1.10.0 affy_1.36.1 Biobase_2.18.0 >> [7] BiocGenerics_0.4.0 >> >> loaded via a namespace (and not attached): >> [1] BiocInstaller_1.8.3 Biostrings_2.26.3 DBI_0.2-5 >> [4] GenomicRanges_1.10.7 IRanges_1.16.6 MASS_7.3-23 >> [7] RSQLite_0.11.2 affxparser_1.30.2 affyio_1.26.0 >> [10] bit_1.1-10 codetools_0.2-8 ff_2.2-11 >> [13] foreach_1.4.0 iterators_1.0.6 oligo_1.22.0 >> [16] oligoClasses_1.20.0 parallel_2.15.2 preprocessCore_1.20.0 >> [19] splines_2.15.2 stats4_2.15.2 tools_2.15.2 >> [22] zlibbioc_1.4.0 >> >> Thanks in advance, >> >> TH >> >> >> -- >> Tae-Hoon Chung, PhD >> >> [[alternative HTML version deleted]] >> >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > -- > Matthew N McCall, PhD > 112 Arvine Heights > Rochester, NY 14611 > Cell: 202-222-5880 > -- Tae-Hoon Chung, PhD [[alternative HTML version deleted]]

It depends a lot on what you plan to do with the preprocessed data. If you wanted to convert gene expression values to gene expression barcodes (see McCall et al. NAR 2011) or anything else where you compare your data to other data sets, then you should just stick with the default fRMA. If this is a pilot study, and you'll eventually have a much larger number of samples, then making your own fRMA vectors might make sense -- here you would want the batch variable to be some combination of lab technician, reagent batch, scan date, etc. Did one person really run 141 arrays on one day? If not, then you don't need to create artificial batches in your data, there are real batch variables that you could consider. Finally, if you are really only interested in looking at these 141 arrays and none of the things I mentioned previously apply, then why not just use RMA? As the error message says, you need to create batches of equal size when creating fRMA vectors. This can actually provide a nice test of how stable your frozen parameters are -- let's say you have batch sizes of 12, 20, 15, and 19, then you could randomly choose 10 arrays from each batch and create your fRMA vectors. You could then repeat this process many times and see how much your frozen parameters change. The following article has a more detailed discussion of the issues in creating fRMA vectors: McCall MN* and Irizarry RA (2011). Thawing Frozen Robust Multi-array Analysis (fRMA), BMC Bioinformatics, 12:369. Best, Matt On Sun, Jun 2, 2013 at 11:00 PM, Tae-Hoon Chung <hoontaechung at="" gmail.com=""> wrote: > Dear Matthew, > > Thanks for your reply. > > I know there's a general purpose library hgu133plus2frmavecs that was > produced using microarray data from diverse tissues and batches. > However, I am interested in a specific tissue only and so don't need to > consider probes that may not be reliable in it. > So I want to know if I need my own version of normalisation parameters based > solely on data from tissue of interest or I can simply rely on general > purpose library at any rate. > I've already processed the data using the general purpose library. > And now it's the turn to develop my own version of normalisation parameters > myself and I came across the error. > > In fact, I tried the procedure with artificially designated two batches. > Interestingly, it also produced an error indicating that the batches were > not of the same size (I split the sample into two batches of sizes 71 and > 70, respectively). > Any suggestion? > > Regards, > TH > > 2013? 5? 31? ???? Matthew McCall<mccallm at="" gmail.com="">?? ??: > >> The issue is that you are trying to estimate between-batch residual >> variances with only 1 batch: >> abatch.ref <- makeVectorsAffyBatch(files.ref, >> rep(1,length(files.ref)), file.dir=FILED) >> >> I'm curious why you are making your own fRMA vectors. HGU133plus2 has >> pre-made frozen parameter vectors in the hgu133plus2frmavecs package, >> so you could use those to preprocess your data. >> >> Best, >> Matt >> >> On Fri, May 31, 2013 at 2:40 AM, Tae-Hoon Chung <hoontaechung at="" gmail.com=""> >> wrote: >>> Hi, all; >>> >>> I encountered the following error while using makeVectorsAffyBatch() >>> function in frmaTools library on 141 Affymetrix HG-U133 Plus 2 chips >>> (single batch). >>> >>> >>> abatch.ref <- makeVectorsAffyBatch(files.ref, rep(1,length(files.ref)), >>> file.dir=FILED) >>> 1 reading GSM493958.CEL ...instantiating an AffyBatch (intensity a >>> 1354896x141 matrix)...done. >>> Reading in : GSM493958.CEL >>> Reading in : GSM493960.CEL >>> Reading in : GSM493965.CEL >>> Reading in : GSM493966.CEL >>> Reading in : GSM493970.CEL >>> >>> ? >>> >>> Reading in : GSM494235.CEL >>> Reading in : GSM494237.CEL >>> Reading in : GSM494240.CEL >>> Data loaded >>> >>> Background Corrected >>> >>> Normalized >>> >>> Beginning Probe Effect Calculation ... >>> >>> Finished probeset: 1000 >>> >>> Finished probeset: 2000 >>> >>> Finished probeset: 3000 >>> >>> Finished probeset: 4000 >>> >>> ? >>> >>> Finished probeset: 53000 >>> >>> Finished probeset: 54000 >>> >>> Probe Effects Calculated >>> >>> Probe Variances Calculated >>> >>> Probe Set SDs Calculated >>> >>> Beginning Median SE Calculation ... >>> >>> Error in if (any(w < 0)) { : missing value where TRUE/FALSE needed >>> >>> >>> Any suggestion? >>> I ran the code under following environment: >>> >>> >>>> sessionInfo() >>> R version 2.15.2 (2012-10-26) >>> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) >>> >>> locale: >>> [1] C >>> >>> attached base packages: >>> [1] stats graphics grDevices utils datasets methods base >>> >>> other attached packages: >>> [1] hgu133plus2cdf_2.11.0 AnnotationDbi_1.20.7 frmaTools_1.10.0 >>> [4] frma_1.10.0 affy_1.36.1 Biobase_2.18.0 >>> [7] BiocGenerics_0.4.0 >>> >>> loaded via a namespace (and not attached): >>> [1] BiocInstaller_1.8.3 Biostrings_2.26.3 DBI_0.2-5 >>> [4] GenomicRanges_1.10.7 IRanges_1.16.6 MASS_7.3-23 >>> [7] RSQLite_0.11.2 affxparser_1.30.2 affyio_1.26.0 >>> [10] bit_1.1-10 codetools_0.2-8 ff_2.2-11 >>> [13] foreach_1.4.0 iterators_1.0.6 oligo_1.22.0 >>> [16] oligoClasses_1.20.0 parallel_2.15.2 preprocessCore_1.20.0 >>> [19] splines_2.15.2 stats4_2.15.2 tools_2.15.2 >>> [22] zlibbioc_1.4.0 >>> >>> Thanks in advance, >>> >>> TH >>> >>> >>> -- >>> Tae-Hoon Chung, PhD >>> >>> [[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 >> >> >> >> -- >> Matthew N McCall, PhD >> 112 Arvine Heights >> Rochester, NY 14611 >> Cell: 202-222-5880 >> > > -- > Tae-Hoon Chung, PhD > -- Matthew N McCall, PhD 112 Arvine Heights Rochester, NY 14611 Cell: 202-222-5880