AnnotatedDataFrame
consists of two parts. There is a collection
of samples and the values of variables measured on those
samples. There is also a description of each variable measured. The
components of an AnnotatedDataFrame
can be accessed with
pData
and varMetadata
.
AnnotatedDataFrame(data, varMetadata, dimLabels=c("rowNames", "columnNames"), ...)
AnnotatedDataFrame
instances are created using
AnnotatedDataFrame
. The function can take three arguments, data
is a
data.frame
of the samples (rows) and measured variables
(columns). varMetadata
is a data.frame
with the number
of rows equal to the number of columns of the data
argument.
varMetadata
describes aspects of each measured
variable. dimLabels
provides aesthetic control for labeling rows
and columns in the show
method. varMetadata
and
dimLabels
can be missing. as(data.frame, "AnnotatedDataFrame")
coerces a data.frame
to an
AnnotatedDataFrame
. annotatedDataFrameFrom
may be a convenient way to create
an AnnotatedDataFrame
from AssayData-class
. data
:data.frame
containing samples (rows)
and measured variables (columns).dimLabels
:character
vector of length 2 that
provides labels for the rows and columns in the show
method.varMetadata
:data.frame
with number of rows
equal number of columns in data
, and at least one column,
named labelDescription
, containing a textual description
of each variable..__classVersion__
:Versions
object describing
the R and Biobase version numbers used to created the instance.
Intended for developer use.as(annotatedDataFrame, "data.frame")
AnnotatedDataFrame
to data.frame
.combine(,
:AnnotatedDataFrame
to a second
AnnotatedDataFrame
, returning the result as an
AnnotatedDataFrame
. Row (sample) names in each argument
must be unique. Variable names present in both arguments occupy a
single column in the resulting AnnotatedDataFrame
. Variable
names unique to either argument create columns with values
assigned for those samples where the variable is
present. varMetadata
in the returned
AnnotatedDataFrame
is updated to reflect the combination.pData()
,
pData()<-
:AnnotatedDataFrame
varMetadata()
,
varMetadata()<-
:AnnotatedDataFrame
featureNames()
,
featureNames()<-
:AnnotatedDataFrame
; a
synonym for sampleNames
.sampleNames()
,
sampleNames()<-
:AnnotatedDataFrame
varLabels()
,
varLabels()<-
:AnnotatedDataFrame
dimLabels()
,
dimLabels() <-
AnnotatedDataFrame
, e.g.,
rowNames, columnNames.initialize()
:new
; not to be called directly by the user.as(, "AnnotatedDataFrame")
:data.frame
to an AnnotatedDataFrame.as(,)
:phenoData-class
objects to
AnnotatedDataFrame
, issuing warnings as appropriate.validObject()
:data
and
varMetadata
elementsupdateObject(object, ..., verbose=FALSE)
updateObject
isCurrent(object)
isCurrent
isVersioned(object)
isVersioned
show()
[,
:AnnotatedDataFrame
, i.e., including relevant
metadata. Unlike a data.frame
, setting drop=TRUE
generates an error. [[
, $
:pData
).[[, ...]]<-
,
$ <-
:pData
. ... can include named arguments (especially
labelDescription
) to be added to varMetadata
.dim()
,
ncol()
:dim
) and variables (ncol
) in the
argument.dimnames()
,
rownames()
,
colnames()
:eSet
, ExpressionSet
,
read.AnnotatedDataFrame
df <- data.frame(x=1:6,
y=rep(c("Low", "High"),3),
z=I(LETTERS[1:6]),
row.names=paste("Sample", 1:6, sep="_"))
metaData <-
data.frame(labelDescription=c(
"Numbers",
"Factor levels",
"Characters"))
AnnotatedDataFrame()
AnnotatedDataFrame(data=df)
AnnotatedDataFrame(data=df, varMetadata=metaData)
as(df, "AnnotatedDataFrame")
obj <- AnnotatedDataFrame()
pData(obj) <- df
varMetadata(obj) <- metaData
validObject(obj)
Run the code above in your browser using DataLab