preprocessing_filtering_and_reduction: Preprocess and filter matrix annotation data project folder...

In vallotlab/ChromSCape: Analysis of single-cell epigenomics datasets with a Shiny App

Preprocess and filter matrix annotation data project folder to SCE

Description

Preprocess and filter matrix annotation data project folder to SCE

Usage

preprocessing_filtering_and_reduction(
  datamatrix,
  annot_raw,
  min_reads_per_cell = 1600,
  max_quantile_read_per_cell = 95,
  n_top_features = 40000,
  norm_type = "CPM",
  n_dims = 10,
  remove_PC = NULL,
  subsample_n = NULL,
  ref_genome = "hg38",
  exclude_regions = NULL,
  doBatchCorr = FALSE,
  batch_sels = NULL
)

Arguments

datamatrix	A sparse count matrix of features x cells.
annot_raw	A data.frame with barcode, cell_id, sample_id, batch_id, total_counts
min_reads_per_cell	Minimum read per cell to keep the cell
max_quantile_read_per_cell	Upper count quantile threshold above which cells are removed
n_top_features	Number of features to keep
norm_type	Normalization type c("CPM", "TFIDF", "RPKM", "TPM", "feature_size_only")
n_dims	An integer specifying the number of dimensions to keep for PCA
remove_PC	A vector of string indicating which principal components to remove before downstream analysis as probably correlated to library size. Should be under the form : 'Component_1', 'Component_2', ... Recommended when using 'TFIDF' normalization method. (NULL)
subsample_n	Number of cells to subsample.
ref_genome	Reference genome ("hg38" or "mm10").
exclude_regions	GenomicRanges with regions to remove from the object.
doBatchCorr	Run batch correction ? TRUE or FALSE
batch_sels	If doBatchCorr is TRUE, List of characters. Names are batch names, characters are sample names.

Value

A SingleCellExperiment object containing feature spaces.

Examples

raw <- create_scDataset_raw()
scExp = preprocessing_filtering_and_reduction(raw$mat, raw$annot)

vallotlab/ChromSCape documentation built on Oct. 15, 2023, 1:47 p.m.