preprocessing: A function to preprocess the list of expression matrix

In SydneyBioX/CiteFuse: CiteFuse: multi-modal analysis of CITE-seq data

A function to preprocess the list of expression matrix

Description

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

Usage

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)

SydneyBioX/CiteFuse documentation built on Feb. 13, 2023, 6:04 a.m.