Deconvolute using MCP-counter

Source: R/immune_deconvolution_methods.R

Deconvolute using MCP-counter

deconvolute_mcp_counter(
  gene_expression_matrix,
  feature_types = "HUGO_symbols",
  log_transform = NULL,
  ...
)

Arguments

gene_expression_matrix

a m x n matrix with m genes and n samples

feature_types

type of identifiers used for expression features. May be one of "affy133P2_probesets","HUGO_symbols","ENTREZ_ID"

log_transform

Controls whether the expression matrix is log2-transformed before running MCP-counter. MCP-counter expects log-transformed data. One of NULL (default), TRUE, or FALSE.

  • NULL – auto-detect: if max(gene_expression_matrix) > 50 the data are assumed to be in linear (TPM) scale and will be log2(x + 1)-transformed.

  • TRUE – always apply log2(x + 1) transformation.

  • FALSE – assume data are already log-transformed; no transformation is applied.

...

passed through to original MCP-counter function. A native argument takes precedence over an immunedeconv argument (e.g. featureType takes precedence over feature_types) See MCPcounter.estimate.