R/SingleCellAssay-methods.R
FromFlatDF.Rd
SingleCellAssay are a generic container for such data and are simple wrappers around SummarizedExperiment objects. Subclasses exist that embue the container with additional attributes, eg FluidigmAssay.
FromFlatDF(dataframe, idvars, primerid, measurement, id = numeric(0), cellvars = NULL, featurevars = NULL, phenovars = NULL, class = "SingleCellAssay", check_sanity = TRUE, ...) FluidigmAssay(...)
dataframe | A 'flattened' |
---|---|
idvars | character vector naming columns that uniquely identify a cell |
primerid | character vector of length 1 that names the column that identifies what feature (i.e. gene) was measured |
measurement | character vector of length 1 that names the column containing the measurement |
id | An identifier (eg, experiment name) for the resulting object |
cellvars | Character vector naming columns containing additional cellular metadata |
featurevars | Character vector naming columns containing additional feature metadata |
phenovars | Character vector naming columns containing additional phenotype metadata |
class | desired subclass of object. Default |
check_sanity | (default: |
... | additional arguments are ignored |
SingleCellAssay, or derived, object
data(vbeta) colnames(vbeta)#> [1] "Sample.ID" "Subject.ID" "Experiment.Number" #> [4] "Chip.Number" "Stim.Condition" "Time" #> [7] "Population" "Number.of.Cells" "Well" #> [10] "Gene" "Ct"vbeta <- computeEtFromCt(vbeta) vbeta.fa <- FromFlatDF(vbeta, idvars=c("Subject.ID", "Chip.Number", "Well"), primerid='Gene', measurement='Et', ncells='Number.of.Cells', geneid="Gene",cellvars=c('Number.of.Cells', 'Population'), phenovars=c('Stim.Condition','Time'), id='vbeta all', class='FluidigmAssay')#>show(vbeta.fa)#> class: FluidigmAssay #> dim: 75 456 #> metadata(0): #> assays(1): Et #> rownames(75): B3GAT1 BAX ... TNFRSF9 TNFSF10 #> rowData names(2): Gene primerid #> colnames(456): Sub01 1 A01 Sub01 1 A02 ... Sub02 3 H10 Sub02 3 H11 #> colData names(9): Number.of.Cells Population ... Time wellKey #> reducedDimNames(0): #> spikeNames(0):nrow(vbeta.fa)#> [1] 75ncol(vbeta.fa)#> [1] 456head(mcols(vbeta.fa)$primerid)#> [1] "B3GAT1" "BAX" "BCL2" "CCL2" "CCL3" "CCL4"table(colData(vbeta.fa)$Subject.ID)#> #> Sub01 Sub02 #> 177 279vbeta.sub <- subset(vbeta.fa, Subject.ID=='Sub01') show(vbeta.sub)#> class: FluidigmAssay #> dim: 75 177 #> metadata(0): #> assays(1): Et #> rownames(75): B3GAT1 BAX ... TNFRSF9 TNFSF10 #> rowData names(2): Gene primerid #> colnames(177): Sub01 1 A01 Sub01 1 A02 ... Sub01 2 H09 Sub01 2 H10 #> colData names(9): Number.of.Cells Population ... Time wellKey #> reducedDimNames(0): #> spikeNames(0):