Deconvolute using ConsesnusTME and a custom signature matrix

Source: R/custom_deconvolution_methods.R

Deconvolute using ConsesnusTME and a custom signature matrix

deconvolute_consensus_tme_custom(
  gene_expression_matrix,
  signature_genes,
  stat_method = "ssgsea"
)

Arguments

gene_expression_matrix

a m x n matrix with m genes and n samples. Data should be TPM normalized and log10 scaled.

signature_genes

a list with each element containing genes to represent a cell type. The cell types should be the names of each element of the list.

stat_method

Choose statistical framework to generate the entichment scores. Default: 'ssgsea'. Available methods: 'ssgsea', 'gsva', 'plage', 'zscore', 'singScore'. These mirror the parameter options of GSVA::gsva() with the exception of singScore which leverages singscore::multiScore()

Note

ConsensusTME uses tumor-specific consensus built gene signatures. In this case only the user-provided signature will be used