geneset_benchmark: perform deconvolution of simulated bulks on different gene...

In MarianSchoen/DMC: Comparison of different Deconvolution Models in several scenarios

perform deconvolution of simulated bulks on different gene sets

Description

perform deconvolution of simulated bulks on different gene sets

Usage

geneset_benchmark(
  training.exprs,
  training.pheno,
  test.exprs,
  test.pheno,
  genesets,
  algorithms,
  bulk.data,
  n.repeats = 3,
  exclude.from.signature = NULL,
  verbose = FALSE,
  cell.type.column = "cell_type",
  patient.column = "patient"
)

Arguments

training.exprs	matrix containing single-cell expression profiles (training set, one cell per column)
training.pheno	data frame containing phenotype data of the single-cell training set. Has to contain column 'cell.type.column'
test.exprs	matrix containing single-cell expression profiles (test set, one cell per column)
test.pheno	data frame containing phenotype data of the single-cell test set. Has to contain column 'cell.type.column'
genesets	list of gene sets (character vectors)
algorithms	List containing a list for each algorithm. Each sublist contains 1) name, 2) function and 3) model
bulk.data	list with two entries: 1) bulks - matrix containing expression data of the bulks (one bulk per column) 2) props - matrix containing the true fractions of cell types within the bulks (cell type x bulk)
n.repeats	integer determining the number of times deconvolution should be repeated for each algorithm, default 3
exclude.from.signature	character vector containing cell types to be excluded from the signature matrix. If not specified, all will be used.
verbose	logical, default FALSE
cell.type.column	string, which column of 'training.pheno'/'test.pheno' holds the cell type information? default "cell_type"
patient.column	string, which column of 'pheno' holds the patient information; optional, default "patient"

Value

list containing deconvolution results for all algorithms for all genesets

MarianSchoen/DMC documentation built on Aug. 2, 2022, 3:05 p.m.