Deconvolution Analysis using MOMF (via Nonnegative Factorization)

Deconvolution Analysis using MOMF (via Nonnegative Factorization)

deconvolute_momf(
  bulk_gene_expression,
  signature,
  single_cell_object,
  verbose = FALSE,
  method = "KL",
  ...
)

Arguments

bulk_gene_expression

A matrix of bulk data. Rows are genes, columns are samples. Row and column names need to be set.

signature

The signature matrix. Rows are genes, columns are cell types.

single_cell_object

A matrix with the single-cell data. Rows are genes, columns are samples. Row and column names need to be set.

verbose

Whether to produce an output on the console.

method

Determines which divergence to use. Options: Kullback-Leibler "KL", Itakura-Saito "IS". Defaults to "KL"

...

additional parameters

Value

cell proportion matrix