mc_es_apply: Multicore apply-like function for cell_data_set

In cole-trapnell-lab/monocle3: Clustering, Differential Expression, and Trajectory Analysis for Single-Cell RNA-Seq

Multicore apply-like function for cell_data_set

Description

mc_es_apply computes the row-wise or column-wise results of FUN, just like esApply. Variables in colData from cds are available in FUN.

Usage

mc_es_apply(
  cds,
  MARGIN,
  FUN,
  required_packages,
  cores = 1,
  convert_to_dense = TRUE,
  reduction_method = "UMAP",
  ...
)

Arguments

cds	A cell_data_set object.
MARGIN	The margin to apply to, either 1 for rows (samples) or 2 for columns (features).
FUN	Any function.
required_packages	A list of packages FUN will need. Failing to provide packages needed by FUN will generate errors in worker threads.
cores	The number of cores to use for evaluation.
convert_to_dense	Whether to force conversion of a sparse matrix to a dense one before calling FUN.
reduction_method	character, the method used to reduce dimension. Default "UMAP".
...	Additional parameters for FUN.

Value

The result of with(colData(cds) apply(counts(cds)), MARGIN, FUN, ...))

cole-trapnell-lab/monocle3 documentation built on April 7, 2024, 9:24 p.m.