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
)

Arguments

exprsMat

A list or a matrix indicates the expression matrices of the testing datasets (each matrix must be matrix or dgCMatrix class)

return_sce

A logical input indicates whether a SingleCellExperiment object will be return

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

Value

either a SingleCellExperiment object or a preprocessed expression matrix

Examples

data(CITEseq_example, package = "CiteFuse") sce_citeseq <- preprocessing(CITEseq_example)