| phenoData {Biobase} | R Documentation |
The class consists of a data.frame and some
accompanying methods suited to handle patient level data for microarrays.
new('phenoData', pData = [data.frame], varLabels = [list], varMetadata = [data.frame])
pData:varLabels:varMetadata:Class-specific methods:
combine(phenoData, phenoData)combineconvertVarLabels(phenoData)getVarMetadata(phenoData, character, character) or getVarMetadata(phenoData, character, missing)pData(phenoData), pData(phenoData)<-pDataphenoData(exprSet)<-phenoData slotsplit(phenoData, vector)split pData and return a list of phenoData objects. Unlike split this function requires the number of rows of pData to be a multiple of the length of vectorvarLabels(phenoData)varMetadata(phenoData)Standard methods defined for 'phenoData':
$(name), $(name, value)<-pData(object)[[as.character(val)]] which does not quite have the right semantics but it is close. This operator extracts the named component of the pData slot in phenoData.[(phenoData)[[(phenoData), [[(phenoData)<-show(phenoData)Functions defined in Biobase to operate with 'phenoData' instances include:
updateObject(object, ..., verbose=FALSE)updateObjectisCurrent(object)isCurrentisVersioned(object)isVersioneddf2pD(x, varLabels, varMetadata)data.frame to a phenoData object. Here x is the data.frame to be coerced; varLabels is a character describing each of the columns in x and varMetadata is a more extensive descriptions of the variables in x, including units of measurement etcread.phenoDataread.phenoDatadata(sample.exprSet) pes <- phenoData(sample.exprSet) pes <- convertVarLabels(pes) varMetadata(pes) # example for 'df2pD' data(cars) d1 = df2pD(cars) # update phenoData to current class description updateObject(phenoData(sample.exprSet))