R/compute_cell_fractions.R

In olapuentesantana/easier_manuscript: Evaluate patient immune response to ICBs through a systems approach

#' Compute immune cell fractions
#'
#' \code{compute_cell_fractions} estimates cell fractions from bulk RNAseq data.
#'
#' @importFrom remotes install_github
#'
#' @export
#'
#' @param RNA.tpm numeric matrix of tpm values with rows=genes and columns=samples
#'
#' @return Cell fractions matrix: matrix of normalized enrichment scores with rows=samples and columns=TFs
#'
#--------------------------------------------------------------------
# Compute cell fractions from transcriptomics data.
#--------------------------------------------------------------------

# This function computes cell fractions from tpm RNAseq data using qaunTIseq method

compute_cell_fractions <- function(RNA.tpm,....){

  # ****************
  # packages
  if(!("BiocManager" %in% installed.packages()[,"Package"])) install.packages("BiocManager", quiet = TRUE)
  list.of.packages <- c("remotes")
  new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
  if(length(new.packages)) BiocManager::install(new.packages, ask = FALSE)

  suppressMessages(remotes::install_github("icbi-lab/immunedeconv"))

  # HGNC symbols are required
  try(if (any(grep("ENSG00000", rownames(RNA.tpm)))) stop("hgnc gene symbols are required", call. = FALSE))

  # Cell fractions: run deconvolute
  cell_fractions <- immunedeconv::deconvolute(gene_expression = RNA.tpm, method = "quantiseq", tumor = TRUE)

  # Samples as rows, TFs as columns
  old_cellnames <- cell_fractions$cell_type
  new_cellnames <- c("B","M1", "M2", "Monocyte", "Neutrophil", "NK", "CD4 T", "CD8+ T", "Treg", "DC", "Other")

  cell_fractions <- t(cell_fractions[,-1])
  colnames(cell_fractions) <- new_cellnames

  message("Cell fractions computed \n")

  return(cell_fractions)
}