binarize_hash_matrix: Binarize a matrix of hash counts

In AllenInstitute/BarMixer: Hashed scRNA-seq demultiplexing for .h5 files

Description

If cutoff values are provided, they will be used. If not, cutoffs will be determined using select_hash_cutoff()

Usage

binarize_hash_matrix(
  mat,
  valid_htos = NULL,
  use_median_cut = FALSE,
  min_cut = 10,
  cutoff_vals = NULL,
  expect_equal_loading = TRUE,
  max_tries = 5
)

Arguments

mat	A matrix or sparse matrix of hash tag oligo counts. Rows must be hashes, columns must be cells
valid_htos	(optional) a character vector of valid hto sequences. Default is NULL, which will use all sequences provided as rownames(mat).
use_median_cut	a logical value indicating whether or not to use the median value of x to set a minimum threshold.
min_cut	a numeric value for the minimum number of counts to consider for select_hash_cutoff(). Default is 10.
cutoff_vals	(optional) a named numeric vector of cutoff values to apply. Length must be equal to nrow(mat), and names must exist in rownames(mat). Default is NULL, which will use select_hash_cutoff() to determine cutoff values.
expect_equal_loading	a logical value indicating if equal loading is expected. This will try to correct overrepresented hashes only (not under-represented). Default is TRUE.
max_tries	a numeric value indicating how many times to attempt adjustment if expect_equal_loading == TRUE to prevent runaway looping. Default is 5

Value

A list containing two objects:

• bmat: a binary sparse matrix (dgCMatrix) with dimensions equal to mat

• bsummary: a data.frame with summary values for each hash tag oligo: hash_barcode, cutoff, n_pos, n_neg, frac_pos, frac_neg

AllenInstitute/BarMixer documentation built on Dec. 17, 2021, 8:42 a.m.