R/convertCellScoresToCounts.R

In Nanostring-Biostats/SpatialDecon: Deconvolution of mixed cells from spatial and/or bulk gene expression data

# SpatialDecon: mixed cell deconvolution for spatial and/or bulk gene expression
# data
# Copyright (C) 2020, NanoString Technologies, Inc.
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#' Convert abundance measurements to cell counts
#'
#' Converts cell abundance scores to cell counts, under the assumption that the
#'  observation with
#'  the greatest sum of cell abundance scores is 100% modelled cells.
#' @param beta Matrix of cell abundance scores, with cells in rows and
#'  observations in columns. The
#'  assumption is that this matrix is from well-normalized data.
#' @param nuclei.counts Optional. A vector of total nuclei counts. If provided,
#' the function will
#'  output not only cells.per.100 but also total cells.
#' @param omit.tumor Logical. If FALSE, any rows of beta with "tumor" in their
#' name will be omitted.
#' @return A list with two elements, each a rescaled version of beta.
#' cells.per.100 gives estimated
#'  percents of total, and cell.counts is cells.per.100 * nuclei.counts.
#' @keywords internal
#' @noRd
convertCellScoresToCounts <- function(beta, nuclei.counts = NULL,
                                      omit.tumor = FALSE) {
    # strip tumor rows if called for:
    if (omit.tumor) {
        beta <- beta[!grepl("tumor", rownames(beta)), , drop = FALSE]
    }
    
    # calc max abundance scores:
    max.total.abundance <- max(colSums(beta))
    
    # calculate rescaled scores:
    out <- list()
    out$cells.per.100 <- beta / max.total.abundance * 100
    if (length(nuclei.counts) == ncol(beta)) {
        out$cell.counts <- sweep(out$cells.per.100, 2, nuclei.counts, "*") / 100
    }
    return(out)
}