plotGroup {ncGTW} | R Documentation

## Plot profiles for each peak group

### Description

This function plots sample profiles with loaded information.

### Usage

    plotGroup(ncGTWinput, sampleRt,
      sampleInd = seq_len(dim(ncGTWinput@rtRaw)[1]), ind = NULL,
      savePath = NULL, show = TRUE, sub = TRUE, filter = FALSE)

### Arguments

`ncGTWinput` | An object return by `loadProfile` of sample profiles for plotting.
`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.
`sampleInd` | Indicate which samples should be plotted, and the default is `1:dim(ncGTWinput$rtRaw)[1]`.
`ind` | A user defined index, and the default is `NULL`.
`savePath` | The path to save the plots, and the default is `NULL` (do not save anything).
`show` | Show the plot in R or not, and the default is `TRUE`.
`sub` | Show more information on the plot or not, and the default is `TRUE`.
`filter` | Apply a Gaussian filter for demonstration or not, and the default is `FALSE`.

### Details

This function plots the extracted ion chromatogram obtained by `loadProfile`. The user can decide to save the figure, show the figure, or apply a Gaussian filter on the data by parameter setting.

### Value

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)

[Package ncGTW version 1.0.0 Index]