R/IPSSMwrapper.R

In papaemmelab/ipssm: Molecular International Prognosis Scoring System For Myelodysplastic Syndromes

#' IPSS-M Wrapper
#'
#' Function that reads, processes, calculates and annotates to output IPSS-M results
#'
#' @param path.file path to the input data file. Allowed formats are .csv, .tsv, .xls, and .xlsx.
#' @param sheet sheet number for excel format input file. Default is 1.
#' @param genesRes a \code{vector} containing the names of the residual genes. Default is from the IPSS-M publised model.
#' @param Nref the average reference value for min(Nres,2) where Nres is the number of mutated residual genes.
#' @param betaValues a covariate vector of the model weights. Should have name attributes.
#' @param meanValues vector of average values for each covariate. Should have the same names attributes as in \code{betaValues}.
#' @param bestValues vector of best values (leading to minimal risk) for each covariate (nRes2 not needed as already taken care of in \code{IPSSMprocess}).
#' @param worstValues vector of worst values (leading to maximal risk) for each covariate (nRes2 not needed as already taken care of in \code{IPSSMprocess}).
#' @param rounding should the raw IPSS-M risk score be rounded. Default is TRUE.
#' @param rounding.digits number of digits for the rounding. Default is 2.
#' @param risk.cutpoints cutpoints to be applied to the IPSS-M risk score to create risk categories.
#' @param risk.cat names of the IPSS-M risk categories.
#' @param range.max threshold for the allowed maximal range in IPSS-M risk (worst - best) to confidently report the mean scenario as the main result. Default 1.
#'
#' @return A patient annoated results \code{data.frame}.
#'
#' @export
#'
#' @examples
#' path.file <- system.file("extdata", "IPSSMexample.csv", package = "ipssm")
#' ddres <- IPSSMwrapper(path.file)
#' print(ddres)
#'
IPSSMwrapper <- function(path.file,
                         sheet = 1,
                         genesRes = c(
                           "BCOR", "BCORL1", "CEBPA", "ETNK1",
                           "GATA2", "GNB1", "IDH1", "NF1",
                           "PHF6", "PPM1D", "PRPF8", "PTPN11",
                           "SETBP1", "STAG2", "WT1"
                         ),
                         Nref = 0.3880,
                         betaValues = c(
                           "HB1" = -0.171, "TRANSF_PLT100" = -0.222, "BLAST5" = 0.352, "CYTOVEC" = 0.287,
                           "TP53multi" = 1.1800, "FLT3" = 0.7980, "MLL_PTD" = 0.7980, "SF3B1_5q" = 0.5040, "NPM1" = 0.4300,
                           "RUNX1" = 0.4230, "NRAS" = 0.4170, "ETV6" = 0.3910,
                           "IDH2" = 0.3790, "CBL" = 0.2950, "EZH2" = 0.2700, "U2AF1" = 0.2470, "SRSF2" = 0.2390, "DNMT3A" = 0.2210,
                           "ASXL1" = 0.2130, "KRAS" = 0.2020, "SF3B1_alpha" = -0.0794,
                           "nRes2" = 0.2310
                         ),
                         meanValues = c(
                           "HB1" = 9.87, "TRANSF_PLT100" = 1.41, "BLAST5" = 0.922, "CYTOVEC" = 1.39,
                           "TP53multi" = 0.0710, "FLT3" = 0.0108, "MLL_PTD" = 0.0247,
                           "SF3B1_5q" = 0.0166, "NPM1" = 0.0112, "RUNX1" = 0.1260, "NRAS" = 0.0362, "ETV6" = 0.0216,
                           "IDH2" = 0.0429, "CBL" = 0.0473, "EZH2" = 0.0588, "U2AF1" = 0.0866, "SRSF2" = 0.1580, "DNMT3A" = 0.1610,
                           "ASXL1" = 0.2520, "KRAS" = 0.0271, "SF3B1_alpha" = 0.1860,
                           "nRes2" = 0.3880
                         ),
                         bestValues = c(
                           "HB1" = 20, "TRANSF_PLT100" = 2.5, "BLAST5" = 0, "CYTOVEC" = 0,
                           "TP53multi" = 0, "FLT3" = 0, "MLL_PTD" = 0,
                           "SF3B1_5q" = 0, "NPM1" = 0, "RUNX1" = 0, "NRAS" = 0, "ETV6" = 0,
                           "IDH2" = 0, "CBL" = 0, "EZH2" = 0, "U2AF1" = 0, "SRSF2" = 0, "DNMT3A" = 0,
                           "ASXL1" = 0, "KRAS" = 0, "SF3B1_alpha" = 1
                         ),
                         worstValues = c(
                           "HB1" = 4, "TRANSF_PLT100" = 0, "BLAST5" = 4, "CYTOVEC" = 4,
                           "TP53multi" = 1, "FLT3" = 1, "MLL_PTD" = 1,
                           "SF3B1_5q" = 1, "NPM1" = 1, "RUNX1" = 1, "NRAS" = 1, "ETV6" = 1,
                           "IDH2" = 1, "CBL" = 1, "EZH2" = 1, "U2AF1" = 1, "SRSF2" = 1, "DNMT3A" = 1,
                           "ASXL1" = 1, "KRAS" = 1, "SF3B1_alpha" = 0
                         ),
                         rounding = TRUE,
                         rounding.digits = 2,
                         risk.cutpoints = c(-1.5, -0.5, 0, 0.5, 1.5),
                         risk.cat = c("Very Low", "Low", "Moderate Low", "Moderate High", "High", "Very High"),
                         range.max = 1) {
  dd <- IPSSMread(path.file)
  dd.process <- IPSSMprocess(patientInput = dd)
  dd.res <- IPSSMmain(patientProcess = dd.process)
  dd.annot <- IPSSMannotate(patientResult = dd.res)

  return(dd.annot)
}