Hi Diana, The first step is to access the data. The GEOquery package provides a way to do this from within R. Alternatively, you can download the CEL files from GEO yourself and read them into R using the affy package. This will produce an AffyBatch object similar to the AffyBatchExample object you used before. Once you have preprocessed (frma) and binarized (barcode) the AffyBatch object, you will need to map the Affy probe ids to Entrez Gene IDs. I believe the best way to do this is still to use the annotation db for the specific Affy platform (e.g. hgu133plus2.db). Hope that helps. Best, Matt On Tue, Nov 14, 2017 at 10:23 AM diana.elassal [bioc] < noreply@bioconductor.org> wrote: > Activity on a post you are following on support.bioconductor.org > > User diana.elassal <https: support.bioconductor.org="" u="" 14392=""/> wrote Question: > Processing several GSM from GEO database using Barcode and fRMA > <https: support.bioconductor.org="" p="" 102985=""/>: > > Hello, > > I am new to R and new to Bioconductor. I have a list of GEO samples (GSMs) > that I would like to process and combine using Barcode in R ( > http://barcode.luhs.org/index.php?page=search) to identify which genes > are expressed or not in my tissue of interest (i.e. binary). > > I installed all the required packages and I used the test data as follows: > > data(AffyBatchExample) > object <- frma(AffyBatchExample) > bc <- barcode(object) > > However, I am not sure how to input my list of GSMs to obtain a single > combined list of unique expressed vs not expressed genes. Ideally, if > possible, using Entrez Gene IDs. I would really appreciate it if anyone > would be able to help me please. > > This is my list of samples: > > GSE8397 (GSM208648, GSM208650, GSM208635, GSM208649, GSM208630, GSM208651, > GSM208647, GSM208632, GSM208633, GSM208631, GSM208652, GSM208646, > GSM208645, GSM208634); GSE7621 (GSM184359, GSM184361, GSM184357, GSM184362, > GSM184354, GSM184355, GSM184360); GSE20292 (GSM508721, GSM508708); > GSE20291(GSM508688); GSE20164 (GSM506014, GSM506020, GSM506019, GSM506023); > GSE20163 (GSM506008, GSM506007, GSM506003, GSM505999, GSM505998, GSM505997, > GSM506001); > > Thank you already so much for any help provided. > > Best wishes, > > Diana > > ------------------------------ > > Post tags: frma, barcode, geneexpression, gsm, ncbi geo > > You may reply via email or visit > Processing several GSM from GEO database using Barcode and fRMA > -- Matthew N McCall, PhD 6 Bridgewood Dr. Fairport, NY 14450 Cell: 202-222-5880