R/compute_TLS.R

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

#' Computation of tertiary lymphoid structures
#' signature (TLS) score
#'
#' Calculates TLS score using the geometric-mean of the
#' expression of its signature genes, as defined in
#' Cabrita et al., Nature, 2020.
#'
#' @references Cabrita, R., Lauss, M., Sanna, A., Donia, M.,
#' Skaarup Larsen, M., Mitra, S., Johansson, I., Phung, B.,
#' Harbst, K., Vallon-Christersson, J., et al. (2020).
#' Tertiary lymphoid structures improve immunotherapy and
#' survival in melanoma. Nature 577, 561–565.
#'
#' @param matches numeric vector indicating the index of
#' signature genes in `RNA_tpm`.
#' @param RNA_tpm data.frame containing TPM values with
#' HGNC symbols in rows and samples in columns.
#'
#' @return A numeric matrix with samples in rows and
#' TLS score in a column.
#'
compute_TLS <- function(matches, RNA_tpm) {
  # Subset RNA_tpm
  sub_RNA_tpm <- RNA_tpm[matches, ]

  # Calculation: geometric mean (so-called log-average)
  # [TPM, 1 offset]
  geom_mean <- apply(sub_RNA_tpm, 2, function(X) exp(mean(log2(X + 1))))

  return(data.frame(TLS = geom_mean, check.names = FALSE))
}