R/ncGTWplot.R

In ncGTW: Alignment of LC-MS Profiles by Neighbor-wise Compound-specific Graphical Time Warping with Misalignment Detection

#' Plot profiles for each peak group
#'
#' This function plots sample profiles with loaded information.
#' @param ncGTWinput An object return by \code{\link{loadProfile}} of sample
#'   profiles for plotting.
#' @param sampleRt A list of the same length as the sample number in which each
#'   element is a vector corresponding to the sample raw/adjusted RT for
#'   plotting.
#' @param sampleInd Indicate which samples should be plotted, and the default is
#'   \code{1:dim(ncGTWinput$rtRaw)[1]}.
#' @param ind A user defined index, and the default is \code{NULL}.
#' @param savePath The path to save the plots, and the default is \code{NULL}
#'   (do not save anything).
#' @param show Show the plot in R or not, and the default is \code{TRUE}.
#' @param sub Show more information on the plot or not, and the default is
#'   \code{TRUE}.
#' @param filter Apply a Gaussian filter for demonstration or not, and the
#'   default is \code{FALSE}.
#'
#' @details This function plots the extracted ion chromatogram obtained by
#' \code{\link{loadProfile}}. The user can decide to save the figure, show the
#' figure, or apply a Gaussian filter on the data by parameter setting.
#' @return A plot to the current device.
#' @examples
#' # obtain data
#' data('xcmsExamples')
#' xcmsLargeWin <- xcmsExamples$xcmsLargeWin
#' xcmsSmallWin <- xcmsExamples$xcmsSmallWin
#' ppm <- xcmsExamples$ppm
#'
#' # detect misaligned features
#' excluGroups <- misalignDetect(xcmsLargeWin, xcmsSmallWin, ppm)
#'
#' # obtain the paths of the sample files
#' filepath <- system.file("extdata", package = "ncGTW")
#' file <- list.files(filepath, pattern="mzxml", full.names=TRUE)
#'
#' tempInd <- matrix(0, length(file), 1)
#' for (n in seq_along(file)){
#'     tempCha <- file[n]
#'     tempLen <- nchar(tempCha)
#'     tempInd[n] <- as.numeric(substr(tempCha, regexpr("example", tempCha) + 7,
#'         tempLen - 6))
#' }
#' # sort the paths by data acquisition order
#' file <- file[sort.int(tempInd, index.return = TRUE)$ix]
#'
#' # load the sample profiles
#' ncGTWinputs <- loadProfile(file, excluGroups)
#'
#' # plot all loaded features
#' for (n in seq_along(ncGTWinputs))
#'     plotGroup(ncGTWinputs[[n]], slot(xcmsLargeWin, 'rt')$corrected)
#' @export

plotGroup <-
    function(ncGTWinput, sampleRt, sampleInd=seq_len(dim(ncGTWinput@rtRaw)[1]),
        ind=NULL, savePath=NULL, show=TRUE, sub=TRUE, filter=FALSE){
    samNum <- dim(ncGTWinput@rtRaw)[1]
    profiles <- ncGTWinput@profiles
    if (filter)
        for (n in seq_len(samNum))
            profiles[n, ] <- gaussFilter(profiles[n, ])

    rtRange <- matrix(0, samNum, dim(ncGTWinput@rtRaw)[2])
    for (n in seq_len(samNum))
        rtRange[n, ] <- sampleRt[[n]][ncGTWinput@rtRaw[n, ]]

    colVec <- matrix(0, samNum, 1)
    for (n in seq_len(dim(colVec)[1]))
        colVec[n] <- rgb(n / samNum, 1 - n / samNum,
            abs(samNum / 2 - abs(n - samNum / 2)) / (samNum / 2))

    mzmed <- round(ncGTWinput@groupInfo['mzmed'], 2)
    groupInd <- ncGTWinput@groupInfo['index']
    tit <- paste("Extracted Ion Chromatogram:", mzmed, "m/z")
    if (!is.null(ind)){
        subt <- paste0("Group ", groupInd, " (", ind, ")",
            "   Color: Green -> Purple -> Red")
    } else{
        subt <- paste0("Group ", groupInd,"   Color: Green -> Purple -> Red")
    }

    if (show){
        matplot(t(rtRange[sampleInd, , drop=FALSE]),
                t(profiles[sampleInd, , drop=FALSE]),
                type='l', col=colVec[sampleInd], lty=1,
                xlab="rt (seconds)", ylab="Intensity")
        if (sub){
            title(main=paste("Extracted Ion Chromatogram:", mzmed, "m/z"),
                sub=subt)
        } else{
            title(main=paste("Extracted Ion Chromatogram:", mzmed, "m/z"))
        }
    }
    if (length(savePath) != 0){
        if (substr(savePath, nchar(savePath), nchar(savePath)) != '/')
            savePath <- paste0(savePath, '/')
        if (ind){
            filePath <- paste0(savePath, "group", groupInd, "_", ind, ".png")
        } else{
            filePath <- paste0(savePath, "group", groupInd, ".png")
        }
        png(filename=filePath, width=1080, height=720)
        matplot(t(rtRange[sampleInd, , drop=FALSE]),
            t(profiles[sampleInd, , drop = FALSE]),
                type='l', col=colVec[sampleInd], lty=1,
                xlab="rt (seconds)", ylab="Intensity")
        if (sub){
            title(main = paste("Extracted Ion Chromatogram:", mzmed, "m/z"),
                sub = subt)
        } else{
            title(main = paste("Extracted Ion Chromatogram:", mzmed, "m/z"))
        }
        dev.off()
    }
}