do_adjustRtime_peakGroups: Align spectrum retention times across samples using peak...

In sneumann/xcms: LC-MS and GC-MS Data Analysis

Align spectrum retention times across samples using peak groups found in most samples

Description

The function performs retention time correction by assessing the retention time deviation across all samples using peak groups (features) containg chromatographic peaks present in most/all samples. The retention time deviation for these features in each sample is described by fitting either a polynomial (smooth = "loess") or a linear (smooth = "linear") model to the data points. The models are subsequently used to adjust the retention time for each spectrum in each sample.

Usage

do_adjustRtime_peakGroups(
  peaks,
  peakIndex,
  rtime = list(),
  minFraction = 0.9,
  extraPeaks = 1,
  smooth = c("loess", "linear"),
  span = 0.2,
  family = c("gaussian", "symmetric"),
  peakGroupsMatrix = matrix(ncol = 0, nrow = 0),
  subset = integer(),
  subsetAdjust = c("average", "previous")
)

Arguments

peaks	a matrix or data.frame with the identified chromatographic peaks in the samples.
peakIndex	a list of indices that provides the grouping information of the chromatographic peaks (across and within samples).
rtime	a list of numeric vectors with the retention times per file/sample.
minFraction	For PeakGroupsParam: numeric(1) between 0 and 1 defining the minimum required proportion of samples in which peaks for the peak group were identified. Peak groups passing this criteria will be aligned across samples and retention times of individual spectra will be adjusted based on this alignment. For minFraction = 1 the peak group has to contain peaks in all samples of the experiment. Note that if subset is provided, the specified fraction is relative to the defined subset of samples and not to the total number of samples within the experiment (i.e., a peak has to be present in the specified proportion of subset samples).
extraPeaks	For PeakGroupsParam: numeric(1) defining the maximal number of additional peaks for all samples to be assigned to a peak group (feature) for retention time correction. For a data set with 6 samples, extraPeaks = 1 uses all peak groups with a total peak count ⁠<= 6 + 1⁠. The total peak count is the total number of peaks being assigned to a peak group and considers also multiple peaks within a sample that are assigned to the group.
smooth	For PeakGroupsParam: character(1) defining the function to be used to interpolate corrected retention times for all peak groups. Can be either "loess" or "linear".
span	For PeakGroupsParam: numeric(1) defining the degree of smoothing (if smooth = "loess"). This parameter is passed to the internal call to loess().
family	For PeakGroupsParam: character(1) defining the method for loess smoothing. Allowed values are "gaussian" and "symmetric". See loess() for more information.
peakGroupsMatrix	optional matrix of (raw) retention times for peak groups on which the alignment should be performed. Each column represents a sample, each row a feature/peak group. If not provided, this matrix will be determined depending on parameters minFraction and extraPeaks. If provided, minFraction and extraPeaks will be ignored.
subset	For ObiwarpParam and PeakGroupsParam: integer with the indices of samples within the experiment on which the alignment models should be estimated. Samples not part of the subset are adjusted based on the closest subset sample. See Subset-based alignment section for details.
subsetAdjust	For ObiwarpParam and PeakGroupsParam: character(1) specifying the method with which non-subset samples should be adjusted. Supported options are "previous" and "average" (default). See Subset-based alignment section for details.

Details

The alignment bases on the presence of compounds that can be found in all/most samples of an experiment. The retention times of individual spectra are then adjusted based on the alignment of the features corresponding to these house keeping compounds. The paraneters minFraction and extraPeaks can be used to fine tune which features should be used for the alignment (i.e. which features most likely correspond to the above mentioned house keeping compounds).

Parameter subset allows to define a subset of samples within the experiment that should be aligned. All samples not being part of the subset will be aligned based on the adjustment of the closest sample within the subset. This allows to e.g. exclude blank samples from the alignment process with their retention times being still adjusted based on the alignment results of the real samples.

Value

A list with numeric vectors with the adjusted retention times grouped by sample.

Note

The method ensures that returned adjusted retention times are increasingly ordered, just as the raw retention times.

Author(s)

Colin Smith, Johannes Rainer

References

Colin A. Smith, Elizabeth J. Want, Grace O'Maille, Ruben Abagyan and Gary Siuzdak. "XCMS: Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification" Anal. Chem. 2006, 78:779-787.

sneumann/xcms documentation built on Nov. 3, 2024, 10:33 p.m.