R/df2dpcr.R

In michbur/dpcR: Digital PCR Analysis

#' Convert data.frame to dpcr object
#'
#' Converts \code{\link{data.frame}} object to to \code{\linkS4class{adpcr}} or
#' \code{\linkS4class{dpcr}} object. The resulting object will have \code{"tnp"}
#' type.
#'
#' @param df data frame with specified column names. See Details.
#' @details The data frame must have REDF structure.
#' It means that data must contain following columns with exactly specified names:
#' \describe{
#' \item{experiment}{names of experiments}
#' \item{replicate}{indices of replicates}
#' \item{assay}{names of assays}
#' \item{k}{number of positive partitions}
#' \item{n}{total number of partitions}
#' \item{v}{volume of partition (nL)}
#' \item{uv}{uncertainty of partition's volume (nL)}
#' \item{threshold}{partitions with \code{k} equal or higher than threshold are
#' treated as positve.}
#' }
#' There are also one optional column:
#' \describe{
#' \item{panel_id}{indices of panels}
#' }
#'
#' If the additional column is present, the resulting object has
#' \code{\linkS4class{adpcr}} type.
#' @return An object of \code{\linkS4class{adpcr}} or \code{\linkS4class{dpcr}} type,
#' depends on the presence of additional column with panel indices (see Details).
#' @seealso Flexibly create \code{\linkS4class{dpcr}} objects: \code{\link{create_dpcr}}
#' Inverse function: \code{\link{dpcr2df}}
#' @author Michal Burdukiewcz, Stefan Roediger
#' @keywords utilities
#' @export
#' @examples
#' dat <- data.frame(
#'   experiment = factor(rep(paste0("Experiment", 1L:2), 3)),
#'   replicate = c(1, 1, 2, 2, 3, 3),
#'   assay = "Assay1",
#'   k = c(55, 121, 43, 150, 70, 131),
#'   n = 765,
#'   v = 1,
#'   uv = 0
#' )
#' df2dpcr(dat)
#'
df2dpcr <- function(df) {
  if (!all(colnames(df) %in% c("experiment", "replicate", "assay", "k", "n", "v", "uv", "threshold")) |
    !all(colnames(df) %in% c("experiment", "replicate", "assay", "k", "n", "v", "uv", "threshold", "panel_id"))) {
    stop("Wrong column names")
  }

  create_dpcr(
    data = matrix(df[["k"]], nrow = 1),
    n = df[["n"]],
    exper = df[["experiment"]],
    replicate = df[["replicate"]],
    assay = df[["assay"]],
    row_names = df[["row_names"]],
    col_names = df[["col_names"]],
    panel_id = df[["panel_id"]],
    v = df[["v"]],
    uv = df[["uv"]],
    adpcr = ncol(df) == 9,
    type = "tnp",
    threshold = df[["threshold"]]
  )
}