mzclust without assuming a certain peak shape.
Includes a baseline subtraction step.
mzpick(MSlist, minpeak = 4, drtsmall = 20, drtfill = 10, drttotal = 200, recurs = 4,
weight = 2, SB = 3, SN=2, minint = 1E4, maxint = 1e+07, ended = 2, progbar = FALSE,
from = FALSE, to = FALSE)mzclustdrtsmallminpeak argumentrecurs, how often can a peak detection fail to end the recursion? drtfill are filled by linear interpolation.
Subsequently, peaks are assigned over a number of recurs recursions not interrupted by more than ended times of failed peak detections. At each recursion, the most intense EIC measurement not yet assigned to a peak is selected as peak apex and neighbouring unassigned measurements at lower and higher RT are evaluated
for forming the peak. To this end, increases (lower RT) and decreases (higher RT) in intensity of consecutive measurements over a maximum RT width of drtdens are summed and
penalized by a factor of weight for intensity reversions. The measurements with optimum values are then selected to define the start and end
measurement of the peak.
Thereupon, the candidate peak is checked to
(a) have at least minpeaks within a RT window of drtsmall,
(b) be larger than the minimum peak intensity minint and
(c) have a minimum SB ratio (the ratio between the most intense measurement and the mimimum intensity of the first or last peak measurement).
Candidate peaks failing in any of the aspects (a) to (c) are discarded (adding to ended), unless they are higher in intensity than maxint.
Next, all measurements assigned to peaks are removed from the EIC and the resulting gaps linearly interpolated and smoothed by a moving window average to form a baseline. The latter is then subtracted from the assigned peaks.
In a last step, peaks are checked for their signal-to-noise SN ratio in relation to the baseline measurements (if present).
Herein, SN is defined as the ratio between the most intense (baseline-corrected) peak measurement and the median of the difference
between the non-peak measurements (if any) and the baseline.
plotMSlist
writePeaklist