R/SingleCellAssay-methods.R
FromMatrix.Rd
If the gene expression measurements are already in a rectangular form, then this function allows an easy way to construct a SingleCellAssay object while still doing some sanity checking of inputs.
FromMatrix(exprsArray, cData, fData, class = "SingleCellAssay", check_sanity = TRUE, check_logged = check_sanity)
exprsArray | matrix, or a list of matrices, or an array. Columns are cells, rows are genes. |
---|---|
cData | cellData an object that can be coerced to a DataFrame, ie, data.frame, AnnotatedDataFrame. Must have as many rows as |
fData | featureData an object that can be coerced to a DataFrame, ie, data.frame, AnnotatedDataFrame. Must have as many rows as |
class | desired subclass of object. Default |
check_sanity | (default: |
check_logged | alias for |
an object of class class
defaultAssay
ncells <- 10 ngenes <- 5 fData <- data.frame(primerid=LETTERS[1:ngenes]) cData <- data.frame(wellKey=seq_len(ncells)) mat <- matrix(rnorm(ncells*ngenes), nrow=ngenes) sca <- FromMatrix(mat, cData, fData)#>#>stopifnot(inherits(sca, 'SingleCellAssay')) stopifnot(inherits(sca, 'SummarizedExperiment')) ##If there are mandatory keywords expected by a class, you'll have to manually set them yourself cData$ncells <- 1 fd <- FromMatrix(mat, cData, fData)#>#>stopifnot(inherits(fd, 'SingleCellAssay'))