Computing cell enrichments for matrix object

Usage

# S3 method for default
postprocess_cell_enrichment(
  input_obj,
  membership_vec,
  num_neigh,
  bool_cosine = T,
  bool_intersect = T,
  max_subsample = min(1000, length(membership_vec)),
  min_deg = 1,
  verbose = 0,
  ...
)

Arguments

input_obj: matrix of n cells and p variable
membership_vec: factor vector of the same length as the number of cells in multiSVD, denoting the cell-types for each cell
num_neigh: number of nearest neighbors
bool_cosine: boolean, for using cosine distance if T or Euclidean distance if F
bool_intersect: boolean, on whether or not to symmetrize (via the AND function) the SNN
max_subsample: maximum of cells to sample for each cell-type. If there are more than max_subsample cells in a cell-type (dictated by membership_vec), a random subset of cells will be selected for the sake of this function
min_deg: minimum degree of each cell in the SNN
verbose: non-negative integer
...: additional arguments