annotateEset(object, x, ...)## S3 method for class 'ExpressionSet,ChipDb':
annotateEset(object, x,
columns = c("PROBEID", "ENTREZID", "SYMBOL", "GENENAME"),
multivals = "first")
## S3 method for class 'ExpressionSet,AffyGenePDInfo':
annotateEset(object, x,
type = "core", ...)
## S3 method for class 'ExpressionSet,AffyHTAPDInfo':
annotateEset(object, x, type = "core",
...)
## S3 method for class 'ExpressionSet,AffyExonPDInfo':
annotateEset(object, x,
type = "core", ...)
## S3 method for class 'ExpressionSet,character':
annotateEset(object, x, ...)
## S3 method for class 'ExpressionSet,data.frame':
annotateEset(object, x, probecol = NULL,
annocols = NULL, ...)
columns
function to see what choices you have. By default we get the ENTREZID, SYMBOL and GENENAME.mapIds
to control how 1:many
mappings are handled. The default is 'first', which takes just the first result. Other valid
values are 'list' and 'CharacterList', which return all mapped results.rma
.object = ExpressionSet,x = ChipDb
: Annotate an ExpressionSet using a ChipDb package for annotation data.object = ExpressionSet,x = AffyGenePDInfo
: Annotate an ExpressionSet using an AffyGenePDInfo package.object = ExpressionSet,x = AffyHTAPDInfo
: Annotate an ExpressionSet using an AffyHTAPDInfo package.object = ExpressionSet,x = AffyExonPDInfo
: Annotate an ExpressionSet using an AffyExonPDInfo package.object = ExpressionSet,x = character
: Method to capture character input.object = ExpressionSet,x = data.frame
: Annotate an ExpressionSet using a user-supplied data.frame.dat <- read.celfiles(filenames = list.celfiles())
eset <- rma(dat)
## annotate using ChipDb
eset <- annotateEset(eset, hgu10sttranscriptcluster.db)
## or AffyGenePDInfo
eset <- annotateEset(eset, pd.hugene.1.0.st.v1)
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