R/compute_Ayers_expIS.R

In olapuentesantana/easier: Estimate Systems Immune Response from RNA-seq data

#' Compute Expanded Immune signature (Ayers_expIS) score
#'
#' Calculates Ayers_expIS score as the average expression
#' of its signature genes, as defined in Ayers et al., J.
#' Clin. Invest, 2017.
#'
#' @references Ayers, M., Lunceford, J., Nebozhyn, M., Murphy,
#' E., Loboda, A., Kaufman, D.R., Albright, A., Cheng, J.D.,
#' Kang, S.P., Shankaran, V., et al. (2017). IFN-y-related mRN
#' A profile predicts clinical response to PD-1 blockade.
#' J. Clin. Invest. 127, 2930–2940.
#' https://doi.org/10.1172/JCI91190.
#'
#' @param matches numeric vector indicating the index of signature
#' genes in `RNA_tpm`.
#' @param RNA_tpm numeric matrix with rows=genes and columns=samples.
#'
#' @return A numeric matrix with rows=samples and
#' columns=Expanded Immune signature score.
#'
compute_Ayers_expIS <- function(matches, RNA_tpm) {
  # Log2 transformation:
  log2_RNA_tpm <- log2(RNA_tpm + 1)

  # Subset log2.RNA_tpm
  sub_log2_RNA_tpm <- log2_RNA_tpm[matches, ]

  # calculation: average of the signature genes
  score <- apply(sub_log2_RNA_tpm, 2, mean)

  return(data.frame(Ayers_expIS = score, check.names = FALSE))
}