GO Analysis for Mouse Exon Array
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@dai-hongying-4801
Last seen 7.3 years ago
Dear friends, I need to perform GO pathway analysis for mouse exon 1.0 ST array using GOstats package. Here what I have done: 1. Read CEL data using oligo package library("pd.moex.1.0.st.v1") library(oligo) affyExonFS <- read.celfiles(list.celfiles()) exonCore <- rma(affyExonFS, target='core') eset<-exprs(exonCore) 2. Detect significant genes using limma package. 3. Find significant pathways using GOstats package. My code is working now, but I still have two questions: 1. Oligo package with pd.moex.1.0.st.v1 annotation does not provide entrez id, gene symbol etc. They provide transcriptclusterid. Does anyone know in my case, after code in step one, how can I map from transcriptclusterid to entrez id when using oligo and pd.moex.1.0.st.v1 annotation packages? 2. I was able to map to entrez id using IPA commercial software. Then in GOstats analysis, I used code params<-new(...,annotation=" mogene10stprobeset.db",...) or params<-new(...,annotation="org.Mm.eg.db",...) hgOver<-hyperGTest(params) Note here I used org.Mm.eg.db and mogene10stprobeset.db package instead of my original pd.moex.1.0.st.v1 ( this does not work for GOstats). The results of significant pathways are slightly different between org.Mm.eg.db and mogene10stprobeset.db. Does anyone recommend one of them or both are fine? Thanks! Daisy Biostatistician ________________________________ Electronic mail from Children's Mercy Hospitals and Clinics. This communication is intended only for the use of the addressee. It may contain information that is privileged or confidential under applicable law. If you are not the intended recipient or the agent of the recipient, you are hereby notified that any dissemination, copy or disclosure of this communication is strictly prohibited. If you have received this communication in error, please immediately forward the message to Children's Mercy Hospital's Information Security Officer via return electronic mail at informationsecurityofficer@cmh.edu and expunge this communication without making any copies. Thank you for your cooperation. [[alternative HTML version deleted]]
Annotation Pathways GO limma GOstats oligo Annotation Pathways GO limma GOstats oligo • 977 views
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@benilton-carvalho-1375
Last seen 20 months ago
Brazil/Campinas/UNICAMP
Hi Daisy, you should be using mogene10sttranscriptcluster.db, given that you summarized to the transcript level ( rma(..., target='core') ). My strategy to get ENTREZID is shown with the script below. HTH, benilton ## preprocess with oligo library(oligo) mogeneFS <- read.celfiles(list.celfiles()) geneCore <- rma(mogeneFS, target='core') psetsInGeneCore <- data.frame(probe_id=featureNames(geneCore)) ## load the transcript annot pkg (note target='core' in rma) library(mogene10sttranscriptcluster.db) annot <- mogene10sttranscriptclusterENTREZID psetsInAnnot <- mappedkeys(annot) ## get ENTREZID when available ENTREZID <- as.data.frame(annot[psetsInAnnot]) ## map the ENTREZID back to the 'probesets' in geneCore obj psetENTREZID <- merge(psetsInGeneCore, ENTREZID, all.x=TRUE) ## ensure that psetENTREZID and geneCore are sorted in the same ## manner idx <- match(featureNames(geneCore), psetENTREZID$probe_id) psetENTREZID <- psetENTREZID[idx,] rownames(psetENTREZID) <- NULL rm(idx) ## get just a random sample n <- nrow(psetENTREZID) psetENTREZID[sort(sample(n, 10)),]
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