I m Thileepan Sekaran Pursuing my Masters in Bioinformatics. Currently I m doing the gene expression profiling of affymetrix data in R. I found the affyexpress package from Bioconductor very interesting and want to use for my analysis but i was stuck when I wanted to find out the differential expressed genes using AffyRegress. The dataset GSE37859 which has been generated in MoGene-1_0-st platform consist of two groups Fibroblast and iNSC cells and I wanted to find the differentially expressed genes between these two groups with fold change of 2 and pvalue of .05.Can any one help me in finding the differantial expressed genes for the dataset btween two groups. -- output of sessionInfo(): "Error in function (classes, fdef, mtable) : unable to find an inherited method for function "annotation", for signature "matrix" -- Sent via the guest posting facility at bioconductor.org.

On Wed, Jun 27, 2012 at 6:19 AM, Thileepan [guest] <guest@bioconductor.org>wrote: > > I m Thileepan Sekaran Pursuing my Masters in Bioinformatics. Currently > I m doing the gene expression profiling of affymetrix data in R. I found > the affyexpress package from Bioconductor very interesting and want to use > for my analysis but i was stuck when I wanted to find out the differential > expressed genes using AffyRegress. The dataset GSE37859 which has been > generated in MoGene-1_0-st platform consist of two groups Fibroblast and > iNSC cells and I wanted to find the differentially expressed genes between > these two groups with fold change of 2 and pvalue of .05.Can any one help > me in finding the differantial expressed genes for the dataset btween two > groups. > > Hello, Thileepan. > -- output of sessionInfo(): > > The output of sessionInfo() should be included in your email. You can get that by pasting in the output after typing "sessionInfo()" into your R session after your error occurs. > "Error in function (classes, fdef, mtable) : > unable to find an inherited method for function "annotation", for > signature "matrix" > > You'll need to send us some code that lets us know how you came to the error. To answer your question directly, though, I'd suggest using the GEOquery package to generate an ExpressionSet for your GSE and then use limma for calculating differential expression. > library(GEOquery) > gse = getGEO("GSE37859")[[1]] I think you'll find your annotation of interest here: > cell_type = pData(gse)$characteristics_ch1 > levels(cell_type) [1] "cell type: induced neural stem cell" [2] "cell type: mouse embryonic fibroblast" [3] "cell type: neural stem cell" If we want to change the levels of the factor, that is possible. > levels(cell_type) = c('iNSC','MEF','NSC') > cell_type V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 iNSC iNSC iNSC iNSC iNSC iNSC NSC NSC NSC MEF MEF MEF You can use that column to design your design matrix in limma. > library(limma) > dm = model.matrix(~ 0 + cell_type) > dm cell_typeiNSC cell_typeMEF cell_typeNSC 1 1 0 0 2 1 0 0 3 1 0 0 4 1 0 0 5 1 0 0 6 1 0 0 7 0 0 1 8 0 0 1 9 0 0 1 10 0 1 0 11 0 1 0 12 0 1 0 attr(,"assign") [1] 1 1 1 attr(,"contrasts") attr(,"contrasts")$cell_type [1] "contr.treatment" >From here, you should be able to follow along in the limma manual. Hope that helps, Sean [[alternative HTML version deleted]]

On Wed, Jun 27, 2012 at 7:26 AM, thileepan sekaran <dena.dinesh@gmail.com>wrote: > Hello Mr.Sean Davis, > > Thank you so much for timely guidance.I m > new to R.Next time I will post with session info information.I tried using > getGEO comannd but it gives an error of "Error in file(con, > "r") : cannot open the connection". > > Session Info() : > > R version 2.12.2 (2011-02-25) > Platform: i386-pc-mingw32/i386 (32-bit) > > locale: > [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United > States.1252 LC_MONETARY=English_United States.1252 LC_NUMERIC=C > > [5] LC_TIME=English_United States.1252 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] GEOquery_2.17.5 ArrayTools_1.10.0 > mogene10sttranscriptcluster.db_6.0.1 org.Mm.eg.db_2.4.6 > > [5] RSQLite_0.10.0 DBI_0.2-5 > AnnotationDbi_1.12.1 AffyExpress_1.16.0 > > [9] limma_3.6.9 mogene10stv1cdf_2.7.0 > affy_1.28.1 vsn_3.18.0 > > [13] Biobase_2.10.0 > > loaded via a namespace (and not attached): > [1] affyio_1.18.0 grid_2.12.2 lattice_0.19-17 > preprocessCore_1.12.0 RCurl_1.5-0.1 tools_2.12.2 > XML_3.2-0.2 > [8] xtable_1.6-0 > > > As I m new to R,your help would be really useful. > > Regards > > Thileepan > > > Hi, Thileepan. Please keep replies on the list. You'll get the best help that way. I hate to do this to you, but your R version is about 3 years old, so I suggest as a first step to update R to the current version and try again. We don't attempt to maintain software that old. If you have problems, please again post sessionInfo(), the code you used (cut-and-paste) and the output/error. Sean > > > On Wed, Jun 27, 2012 at 12:40 PM, Sean Davis <sdavis2@mail.nih.gov> wrote: > >> >> >> On Wed, Jun 27, 2012 at 6:19 AM, Thileepan [guest] < >> guest@bioconductor.org> wrote: >> >>> >>> I m Thileepan Sekaran Pursuing my Masters in Bioinformatics. >>> Currently I m doing the gene expression profiling of affymetrix data in R. >>> I found the affyexpress package from Bioconductor very interesting and want >>> to use for my analysis but i was stuck when I wanted to find out the >>> differential expressed genes using AffyRegress. The dataset GSE37859 which >>> has been generated in MoGene-1_0-st platform consist of two groups >>> Fibroblast and iNSC cells and I wanted to find the differentially expressed >>> genes between these two groups with fold change of 2 and pvalue of .05.Can >>> any one help me in finding the differantial expressed genes for the dataset >>> btween two groups. >>> >>> >> Hello, Thileepan. >> >> >>> -- output of sessionInfo(): >>> >>> >> The output of sessionInfo() should be included in your email. You can >> get that by pasting in the output after typing "sessionInfo()" into your R >> session after your error occurs. >> >> >>> "Error in function (classes, fdef, mtable) : >>> unable to find an inherited method for function "annotation", for >>> signature "matrix" >>> >>> >> You'll need to send us some code that lets us know how you came to the >> error. >> >> To answer your question directly, though, I'd suggest using the GEOquery >> package to generate an ExpressionSet for your GSE and then use limma for >> calculating differential expression. >> >> > library(GEOquery) >> > gse = getGEO("GSE37859")[[1]] >> >> I think you'll find your annotation of interest here: >> >> > cell_type = pData(gse)$characteristics_ch1 >> > levels(cell_type) >> [1] "cell type: induced neural stem cell" >> [2] "cell type: mouse embryonic fibroblast" >> [3] "cell type: neural stem cell" >> >> If we want to change the levels of the factor, that is possible. >> >> > levels(cell_type) = c('iNSC','MEF','NSC') >> > cell_type >> V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 >> iNSC iNSC iNSC iNSC iNSC iNSC NSC NSC NSC MEF MEF MEF >> >> You can use that column to design your design matrix in limma. >> >> > library(limma) >> > dm = model.matrix(~ 0 + cell_type) >> > dm >> cell_typeiNSC cell_typeMEF cell_typeNSC >> 1 1 0 0 >> 2 1 0 0 >> 3 1 0 0 >> 4 1 0 0 >> 5 1 0 0 >> 6 1 0 0 >> 7 0 0 1 >> 8 0 0 1 >> 9 0 0 1 >> 10 0 1 0 >> 11 0 1 0 >> 12 0 1 0 >> attr(,"assign") >> [1] 1 1 1 >> attr(,"contrasts") >> attr(,"contrasts")$cell_type >> [1] "contr.treatment" >> >> From here, you should be able to follow along in the limma manual. >> >> Hope that helps, >> >> Sean >> >> > [[alternative HTML version deleted]]