mzclust and mzpick;
altenative to mzagglom.
Requires an MSlist initilialized by readMSdata as input.
mzpart(MSlist, dmzgap = 10, drtgap = 500, ppm = TRUE,
minpeak = 4, peaklimit = 2500, cutfrac = 0.1, drtsmall=50,
progbar = FALSE, stoppoints = 2e+05)readMSdatadmzgap given in ppm (TRUE) or as absolute value (FALSE)?minpeak bigger than its counterpart in mzclust or mzpick.
Too complicated? Then rather use enviPickwrap for adjusting all function arguments.plotMSlist to have a look at your
data contained in MSlist after upload with readMSdata;
set progbar=TRUE to monitor where a function fails. Once settled, set progbar=FALSE for faster execution. To avoid running out of memory, stoppoints sets the maximum number of measurements that can be handled in the routines to delete
those of lowest intensity (in cases where peaklimit cannot be reached by partitioning by dmzgap and drtgap alone).
If above stoppoints, execution aborts.cutfrac of
lowest-density measurements is discarded and the partition procedure resumed. Measurement-wise density is based on a gaussian kernel density estimate
scaled to dmzgap and drtsmall, i.e., to the local neighbourhood of each measurement.Partitioning is necessary to speed up the clustering procedure of mzclust. Hence, there is a trade-off:
large values of peaklimit leads to faster execution of
mzpart but to slower computation of mzclust and vice versa.
mzclust