R/clean_Skyline.R

In MSstatsConvert: Import Data from Various Mass Spectrometry Signal Processing Tools to MSstats Format

#' Clean raw data from Skyline
#' @param msstats_object an object of class `MSstatsSpectroMineFiles`.
#' @return data.table
#' @keywords internal
.cleanRawSkyline = function(msstats_object) {
    Truncated = isZero = DetectionQValue = Intensity = NULL
    
    sl_input = getInputFile(msstats_object, "input")
    data.table::setnames(sl_input, c("FileName", "Area"),
                         c("Run", "Intensity"), skip_absent = TRUE)
    
    sl_input = sl_input[, !(colnames(sl_input) == "PeptideSequence"), 
                        with = FALSE]
    data.table::setnames(sl_input, "PeptideModifiedSequence",
                         "PeptideSequence", skip_absent = TRUE)
    suppressWarnings({
        sl_input[, Intensity := as.numeric(as.character(Intensity))]
    })
    if (is.element("DetectionQValue", colnames(sl_input))) {
        sl_input[, DetectionQValue := as.numeric(as.character(DetectionQValue))]
    }
    if (is.character(sl_input$Truncated) | is.factor(sl_input$Truncated)) {
        sl_input[, Truncated := as.character(Truncated) == "True"]
    }
    sl_input[, Truncated := as.character(Truncated)]
    
    sl_cols = c("ProteinName", "PeptideSequence", "PrecursorCharge", 
                "FragmentIon", "ProductCharge", "IsotopeLabelType", "Condition",
                "BioReplicate", "Run", "Intensity", "StandardType")
    sl_cols = c(sl_cols, "Fraction", "DetectionQValue", "Truncated")
    sl_input = sl_input[, intersect(sl_cols, colnames(sl_input)), with = FALSE]
    sl_input[, isZero := ((Intensity == 0) | (Intensity < 1)) & !is.na(Intensity)]
    .logSuccess("Skyline", "clean")
    sl_input
}


#' Handle isotopic peaks
#' @param input data.table preprocessed by one of the `cleanRaw*` functions.
#' @param aggregate if TRUE, isotopic peaks will be summed.
#' @return data.table
#' @keywords internal
.handleIsotopicPeaks = function(input, aggregate = FALSE) {
    FragmentIon = ProductCharge = NULL
    
    if (aggregate) {
        input$isZero = ifelse(input$Intensity == 0, TRUE, input$isZero)
        if (.checkDDA(input)) {
            feature_cols = c("ProteinName", "PeptideSequence", "PrecursorCharge", 
                             "Run")
            feature_cols = c(feature_cols, c("BioReplicate", "Condition", "StandardType", 
                                             "IsotopeLabelType", "DetectionQValue"))
            feature_cols = intersect(feature_cols, colnames(input))
            input = .summarizeMultipleMeasurements(input, sum, feature_cols)
            input[, FragmentIon := NA]
            input[, ProductCharge := NA]
            getOption("MSstatsLog")("INFO", "** Three isotopic preaks per feature and run are summed")
            getOption("MSstatsMsg")("INFO", "** Three isotopic preaks per feature and run are summed")
        }
    }
    input
}


#' Check validity of DDA data
#' @param input data.table preprocessed by one of the `cleanRaw*` functions.
#' @return logical
#' @return logical, TRUE means that the `input` dataset comes from a DDA experiment
#' @keywords internal
.checkDDA = function(input) {
    fragment_ions = as.character(unique(input[["FragmentIon"]]))
    check_DDA = setdiff(c("precursor", "precursor [M+1]", "precursor [M+2]"), 
                        fragment_ions)
    frags = setdiff(fragment_ions, 
                    c('precursor', 'precursor [M+1]', 'precursor [M+2]'))
    precursors = intersect(fragment_ions, 
                           c("precursor", "precursor [M+1]", "precursor [M+2]"))
    if (length(frags) > 0 & length(precursors) > 0) {
        msg = paste("** Please check precursors information.",
                    "If your experiment is DIA, please remove the precursors.",
                    "If your experiments is DDA, please check the precursor information.")
        getOption("MSstatsLog")("ERROR", msg)
        stop(msg)
    }
    length(check_DDA) < 3
}