Picking Peaks#

For low resolution data, consider to smooth the data first (Smoothing raw data) and subtract the baseline (Subtracting a baseline from a spectrum) before peak picking.

There are two types of PeakPickers: the PeakPickerWavelet and one especially suited for high resolution data (PeakPickerHiRes). This tutorial explains the PeakPickerWavelet. Use the file peakpicker_tutorial_2.mzML from the examples data (select File > Open example data).

The main parameters are the peak width and the minimal signal to noise ratio for a peak to be picked. If you don’t know the approximate fwhm of peaks, use the estimation included in the PeakPickerWavelet, set the flag estimate_peak_width to true. After applying the PeakPickerWavelet, observe which peak width was estimated and used for peak picking in the log window.

To estimate the peak width, use the measuring tool Action Modes and Their Uses to determine the fwhm of one or several representative peaks.

If the peak picker delivers only a few peaks even though the peak_with and signal_to_noise parameters are set to good values, consider changing the advanced parameter fwhm_lower_bound_factor to a lower value. All peaks with a lower fwhm than fwhm_lower_bound_factor * peak_width are discarded.

The following image shows a part of the spectrum with the picked peaks shown in green, the estimated peak width in the log window and the measured peak width.

TOPPView tools pppicked