Create a sparse count matrix from various format of input data.

Source: R/preprocessing_filtering_reduction.R

This function takes three different type of single-cell input: - Single cell BAM files (sorted) - Single cell BED files (gzipped) - A combination of an index file, a peak file and cell barcode file (The index file is composed of three column: index i, index j and value x for the non zeroes entries in the sparse matrix.)

raw_counts_to_sparse_matrix(
  files_dir_list,
  file_type = c("scBED", "scBAM", "FragmentFile"),
  use_Signac = TRUE,
  peak_file = NULL,
  n_bins = NULL,
  bin_width = NULL,
  genebody = NULL,
  extendPromoter = 2500,
  verbose = TRUE,
  ref = c("hg38", "mm10")[1],
  progress = NULL,
  BPPARAM = BiocParallel::bpparam()
)

Arguments

files_dir_list

A named character vector of directories containing the files. The names correspond to sample names.
file_type

Input file(s) type(s) ('scBED','scBAM','FragmentFile')
use_Signac

Use Signac wrapper function 'FeatureMatrix' if the Signac package is installed (TRUE).
peak_file

A file containing genomic location of peaks (NULL)
n_bins

The number of bins to tile the genome (NULL)
bin_width

The size of bins to tile the genome (NULL)
genebody

Count on genes (body + promoter) ? (NULL)
extendPromoter

If counting on genes, number of base pairs to extend up or downstream of TSS (2500).
verbose

Verbose (TRUE)
ref

reference genome to use (hg38)
progress

Progress object for Shiny
BPPARAM

BPPARAM object for multiprocessing. See bpparam for more informations. Will take the default BPPARAM set in your R session.

Source

Value

A sparse matrix of features x cells

Details

This functions re-counts signal on either fixed genomic bins, a set of user-defined peaks or around the TSS of genes.

References

Stuart el al., Multimodal single-cell chromatin analysis with Signac bioRxiv https://doi.org/10.1101/2020.11.09.373613