For each sample, identify peak groups where that sample is not represented. For each of those peak groups, integrate the signal in the region of that peak group and create a new peak.
(DEPRECATED): number of slaves/cores to be used for
parallel peak filling.
MPI is used if installed, otherwise the snow package is employed for
multicore support. If none of the two packages is available it uses
the parallel package for parallel processing on multiple CPUs of the
current machine. Users are advised to use the
Expansion factor for the m/z range used for integration.
Expansion factor for the rentention time range used for integration.
allows to define a specific parallel processing setup
for the current task (see
After peak grouping, there will always be peak groups that do not include peaks from every sample. This method produces intensity values for those missing samples by integrating raw data in peak group region. In a given group, the start and ending retention time points for integration are defined by the median start and end points of the other detected peaks. The start and end m/z values are similarly determined. Intensities can be still be zero, which is a rather unusual intensity for a peak. This is the case if e.g. the raw data was threshholded, and the integration area contains no actual raw intensities, or if one sample is miscalibrated, such thet the raw data points are (just) outside the integration area.
Importantly, if retention time correction data is available, the alignment information is used to more precisely integrate the propper region of the raw data. If the corrected retention time is beyond the end of the raw data, the value will be not-a-number (NaN).
xcmsSet objects with filled in peak groups (into and maxo).
BPPARAM = bpparam())
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