refineChromPeaks-merge: Merge neighboring and overlapping chromatographic peaks
In yclement/xcms: LC-MS and GC-MS Data Analysis

Description Usage Arguments Details Value Note Author(s) See Also Examples

Peak detection sometimes fails to identify a chromatographic peak correctly, especially for broad peaks and if the peak shape is irregular (mostly for HILIC data). In such cases several smaller peaks are reported. Also, peak detection can result in partially or completely overlapping peaks. To reduce such peak detection artifacts, this function merges chromatographic peaks which are overlapping or close in rt and m/z dimension considering also the measured signal intensities in the region between them.

Chromatographic peaks are first expanded in m/z and retention time dimension (based on parameters expandMz, ppm and expandRt) and subsequently grouped into sets of merge candidates if they are (after expansion) overlapping in both m/z and rt (within the same sample). Candidate peaks are merged if the average intensity of the 3 data points in the middle position between them (i.e. at half the distance between "rtmax" of the first and "rtmin" of the second peak) is larger than a certain proportion (minProp) of the smaller maximal intensity ("maxo") of both peaks. In cases in which this calculated mid point is not located between the apexes of the two peaks (e.g. if the peaks are largely overlapping) the average signal intensity at half way between the apexes is used instead. Candidate peaks are not joined if all 3 data points between them have NA intensities. The joined peaks get the "mz", "rt", "sn" and "maxo" values from the peak with the largest signal ("maxo") as well as its row in the metadata data frame of the peak (chromPeakData). The "rtmin", "rtmax" of the merged peaks are updated and "into" is recalculated based on all the signal between "rtmin" and "rtmax" of the new merged peak. See details for information on the "mzmin" and "mzmax" values of the merged peak.

MergeNeighboringPeaksParam(
  expandRt = 2,
  expandMz = 0,
  ppm = 10,
  minProp = 0.75
)

## S4 method for signature 'XCMSnExp,MergeNeighboringPeaksParam'
refineChromPeaks(
  object,
  param = MergeNeighboringPeaksParam(),
  msLevel = 1L,
  BPPARAM = bpparam()
)

`expandRt`	`numeric(1)` defining by how many seconds the retention time window is expanded on both sides to check for overlapping peaks.
`expandMz`	`numeric(1)` constant value by which the m/z range of each chromatographic peak is expanded (on both sides!) to check for overlapping peaks.
`ppm`	`numeric(1)` defining a m/z relative value (in parts per million) by which the m/z range of each chromatographic peak is expanded to check for overlapping peaks.
`minProp`	`numeric(1)` between `0` and `1` representing the proporion of intensity to be required for peaks to be joined. See description for more details. The default (`minProp = 0.75`) means that peaks are only joined if the signal half way between then is larger 75% of the smallest of the two peak's `"maxo"` (maximal intensity at peak apex).
`object`	XCMSnExp object with identified chromatographic peaks.
`param`	`MergeNeighboringPeaksParam` object defining the settings for the method.
`msLevel`	`integer` defining for which MS level(s) the chromatographic peaks should be merged.
`BPPARAM`	parameter object to set up parallel processing. Uses the default parallel processing setup returned by `bpparam()`. See `bpparam()` for details and examples.

For each set of candidate peaks an ion chromatogram is extracted using the range of retention times and m/z values of these peaks. The m/z range for the extracted ion chromatogram is expanded by expandMz and ppm (on both sides) to reduce the possibility of missing signal intensities between candidate peaks (variance of measured m/z values for lower intensities is larger than for higher intensities and thus data points not being part of identified chromatographic peaks tend to have m/z values outside of the m/z range of the candidate peaks - especially for ToF instruments). This also ensures that all data points from the same ion are considered for the peak integration of merged peaks. The smallest and largest m/z value of all data points used in the peak integration of the merged peak are used as the merged peak's m/z range (i.e. columns "mzmin" and "mzmax").

XCMSnExp object with chromatographic peaks matching the defined conditions being merged.

Note that each peak gets expanded by expandMz and expandRt, thus peaks differing by 2 * expandMz (or expandRt) will be identified as overlapping. As an example: m/z max of one peak is 12.2, m/z min of another one is 12.4, if expandMz = 0.1 the m/z max of the first peak will be 12.3 and the m/z min of the second one 12.3, thus both are considered overlapping.

refineChromPeaks methods will always remove feature definitions, because a call to this method can change or remove identified chromatographic peaks, which may be part of features.

Merging of chromatographic peaks is performed along the retention time axis, i.e. candidate peaks are first ordered by their "rtmin" value. The signals at half way between the first and the second candidate peak are then compared to the smallest "maxo" of both and the two peaks are then merged if the average signal between the peaks is larger minProp. For merging any additional peak in a candidate peak list the "maxo" of that peak and the newly merged peak are considered.

Johannes Rainer, Mar Garcia-Aloy

Other chromatographic peak refinement methods: CleanPeaksParam

xd <- readMSData(system.file('cdf/KO/ko15.CDF', package = "faahKO"),
    mode = "onDisk")
xd <- findChromPeaks(xd, param = CentWaveParam(prefilter = c(5, 10000),
    noise = 5000))

## Example of a split peak that will be merged
mzr <- 305.1 + c(-0.01, 0.01)
chr <- chromatogram(xd, mz = mzr)
plot(chr)

## Combine the peaks
res <- refineChromPeaks(xd, param = MergeNeighboringPeaksParam(expandRt = 4))
chr_res <- chromatogram(res, mz = mzr)
plot(chr_res)

## Example of a peak that was not merged, because the signal between them
## is lower than the cut-off minProp
mzr <- 496.2 + c(-0.01, 0.01)
chr <- chromatogram(xd, mz = mzr)
plot(chr)
chr_res <- chromatogram(res, mz = mzr)
plot(chr_res)