intersection between genes and pathways
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@alberto-goldoni-3477
Last seen 9.6 years ago
Dear all, i have a question for you. If i have a list of 66 genes: > SHR ExpressionSet (storageMode: lockedEnvironment) assayData: 66 features, 4 samples element names: exprs phenoData sampleNames: SHR-PUFA5.CEL, SHR-PUFA6.CEL, SHR-st7.CEL, SHR-st8.CEL varLabels and varMetadata description: DIETA: Con PUFA=OMEGA3 o ST=ALIMENTAZIONE STANDARD TYPE: WK=RATTO NORMALE o SHR=RATTO IPERTESO featureData featureNames: 1367871_at, 1368692_a_at, ..., 1399089_at (66 total) fvarLabels and fvarMetadata description: none experimentData: use 'experimentData(object)' Annotation: rat2302 and i would found which genes are involved in the "hypertrophy" and "cardiac decompensation" pathways. the only way i have found is to list all the pathways with my probe ids: paths <- aafPathway(probeids, "rat2302.db") but now i have to look manually to every pathway. There is a method in order to do automatically, because now i have only 66 genes, but if i have 1000 genes is too complicated. Best regards. -- ----------------------------------------------------- Dr. Alberto Goldoni Bologna, Italy
Pathways Pathways • 878 views
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John Stevens ▴ 30
@john-stevens-3739
Last seen 9.6 years ago
Hi Alberto, There may be a more elegant way to do this, but I think you'll want to make use of the rat2302PATH2PROBE object in the rat2302.db package. The key is that you first need the path ID, and that's available through the KEGG.db package. Below is some starter code; I hope it helps. Regards, John R. Stevens Utah State University # load KEGG pathway information library(KEGG.db) # define a function to search for path IDs # - shouldn't need to change this KEGGTerm2Tag <- function(term) { KTL <- eapply(KEGGPATHID2NAME, function(x){agrep(term,x,value=TRUE)}) Kl <- sapply(KTL,length); names(KTL[Kl>0]) } # call this function -- look for path ID of pathways # whose name contains 'hyptertroph' KEGG <- KEGGTerm2Tag("hyptertroph") KEGG # "05410" # see full name of this path ID KEGGPATHID2NAME$"05410" # "Hypertrophic cardiomyopathy (HCM)" # get probeset IDs from rat2302 array # that are in this pathway library(rat2302.db) gn <- rat2302PATH2PROBE$"05410" # Then look at the intersection of this vector # and the vector of probeset IDs # from your ExpressionSet object SHR intersect(gn,featureNames(SHR)) -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor- bounces@stat.math.ethz.ch] On Behalf Of Alberto Goldoni Sent: Wednesday, March 10, 2010 2:45 AM To: BioC Subject: [BioC] intersection between genes and pathways Dear all, i have a question for you. If i have a list of 66 genes: > SHR ExpressionSet (storageMode: lockedEnvironment) assayData: 66 features, 4 samples element names: exprs phenoData sampleNames: SHR-PUFA5.CEL, SHR-PUFA6.CEL, SHR-st7.CEL, SHR-st8.CEL varLabels and varMetadata description: DIETA: Con PUFA=OMEGA3 o ST=ALIMENTAZIONE STANDARD TYPE: WK=RATTO NORMALE o SHR=RATTO IPERTESO featureData featureNames: 1367871_at, 1368692_a_at, ..., 1399089_at (66 total) fvarLabels and fvarMetadata description: none experimentData: use 'experimentData(object)' Annotation: rat2302 and i would found which genes are involved in the "hypertrophy" and "cardiac decompensation" pathways. the only way i have found is to list all the pathways with my probe ids: paths <- aafPathway(probeids, "rat2302.db") but now i have to look manually to every pathway. There is a method in order to do automatically, because now i have only 66 genes, but if i have 1000 genes is too complicated. Best regards. -- ----------------------------------------------------- Dr. Alberto Goldoni Bologna, Italy _______________________________________________ Bioconductor mailing list Bioconductor at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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