[BioC] intersection between genes and pathways
john.r.stevens at usu.edu
Thu Mar 11 01:06:52 CET 2010
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.
John R. Stevens
Utah State University
# load KEGG pathway information
# define a function to search for path IDs
# - shouldn't need to change this
KEGGTerm2Tag <- function(term)
KTL <- eapply(KEGGPATHID2NAME,
Kl <- sapply(KTL,length); names(KTL[Kl>0])
# call this function -- look for path ID of pathways
# whose name contains 'hyptertroph'
KEGG <- KEGGTerm2Tag("hyptertroph")
# see full name of this path ID
# "Hypertrophic cardiomyopathy (HCM)"
# get probeset IDs from rat2302 array
# that are in this pathway
gn <- rat2302PATH2PROBE$"05410"
# Then look at the intersection of this vector
# and the vector of probeset IDs
# from your ExpressionSet object SHR
From: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Alberto Goldoni
Sent: Wednesday, March 10, 2010 2:45 AM
Subject: [BioC] intersection between genes and pathways
i have a question for you.
If i have a list of 66 genes:
ExpressionSet (storageMode: lockedEnvironment)
assayData: 66 features, 4 samples
element names: exprs
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)'
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.
Dr. Alberto Goldoni
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