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Targeted feature detection


Feature detection → LC-MS → Targeted feature detection

This algorithm opens a .csv file with a list of peaks and searches for each peak in the selected raw data file. The most crucial parameters are m/z tolerance and Retention time tolerance*, which define the window where the algorithm should find the new peak. It is centered in the m/z average and retention time average of the source peak list. Once the best candidate is found inside the window, its shape in RT direction is also checked.

The *.csv file should have three columns:

  • The first column should contain the expected M/Z,
  • the second column the expected RT,
  • and the third the peak name.

⚠ Each peak should be in a different row.


Name suffix

Suffix to be added to the peak list name.

Peak list file

Path of the csv file containing the list of peaks to be detected.

Field separator

Character(s) used to separate fields in the peak list file.

Ignore first line

Check to ignore the first line of peak list file.

Intensity tolerance

This value sets the maximum allowed deviation from expected shape of a peak in chromatographic direction.

Noise level

The minimum intensity level for a data point to be considered part of a chromatogram. All data points below this intensity level are ignored.

m/z Tolerance

Maximum allowed m/z difference to find the peak

Retention time tolerance

Maximum allowed retention time difference to find the peak


Last update: November 24, 2022 21:13:07