This function will keep the samples that are
common across the list of expression matrix,
and filter the features that are all zeros across samples,
and finally construct a SingleCellExperiment
object
preprocessing( exprsMat = NULL, return_sce = TRUE, assay_matrix = 1, filter_features = TRUE, rowData = NULL, colData = NULL )
exprsMat | A list or a matrix indicates the expression matrices of the
testing datasets (each matrix must be |
---|---|
return_sce | A logical input indicates whether
a |
assay_matrix | A integer indicates which list will be used as `assay` input of `SingleCellExperiment` |
filter_features | A logical input indicates whether the features with all zeros will be removed |
rowData | A DataFrame indicates the rowData to be stored in the sce object |
colData | A DataFrame indicates the colData to be stored in the sce object |
either a SingleCellExperiment object or a preprocessed expression matrix