PeakGroupsPar: Peak density parameters
In sipss/AlpsLCMS: Signal processing of LC-MS metabolomics

The method creates a template with the parameters for alignment. Extracted from the function xcms::PeakGroupsParam.

1	PeakGroupsPar(...)

...

Arguments passed on to xcms::PeakGroupsParam

minFraction: numeric(1) between 0 and 1 defining the minimum required fraction of samples in which peaks for the peak group were identified. Peak groups passing this criteria will 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: numeric(1) defining the maximal number of additional peaks for all samples to be assigned to a peak group (i.e. 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 being assigned to the group.
smooth: character defining the function to be used, to interpolate corrected retention times for all peak groups. Either "loess" or "linear".
span: numeric(1) defining the degree of smoothing (if smooth = "loess"). This parameter is passed to the internal call to loess.
family: character defining the method to be used for loess smoothing. Allowed values are "gaussian" and "symmetric".See loess for more information.
peakGroupsMatrix: optional matrix of (raw) retention times for the peak groups on which the alignment should be performed. Each column represents a sample, each row a feature/peak group. Such a matrix is for example returned by the adjustRtimePeakGroups method.
subset: 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 description above for more details.
subsetAdjust: character specifying the method with which non-subset samples should be adjusted. Supported options are "previous" and "average" (default). See description above for more information.