A few python scripts for metabolomics.
The script takes as input a list of features to be deleted and the MGF file from feature-based molecular networking (FBMN). As output, a filtered MGF with spectra for only the feature IDs of interest is generated. This file can then be used to generate a FBMN that was prefiltered.
NOTE: It is important to also filter the Feature Table (.csv file) exported from MZmine, so that the features in both files match.
Interative notebook here ->
The script: filter_mgf_MZmine.py
This script takes as input the sirius.mgf file exported from MZmine3, which contains SPECTYPE=CORRELATED MS for some MS1 - this causes an error in Qemistree when converting the mgf file to qza (Feature "1" has more than one MSLEVEL=1 record). As output, a new sirius.mgf file is generated, in which the SPECTYPE=CORRELATED MS are removed.
The script: SIRIUS export MZmine3_SPECTYPE removal.ipynb