I found this documentation on pyOpenMS mass spec library. I want to try different peak picking algorithms. Unfortunately, the docs are not very detailed and don't show how to use the other peak picking algorithms and the codebase itself is also quite cryptic for me.
Any idea how to use, for example, the FeatureFindingMetabo algorithm insead of the centroided one?
from urllib.request import urlretrieve # from urllib import urlretrieve # use this code for Python 2.x gh = "https://raw.githubusercontent.com/OpenMS/OpenMS/develop" urlretrieve (gh +"/src/tests/topp/FeatureFinderCentroided_1_input.mzML", "feature_test.mzML") from pyopenms import * # Prepare data loading (save memory by only # loading MS1 spectra into memory) options = PeakFileOptions() options.setMSLevels() fh = MzMLFile() fh.setOptions(options) # Load data input_map = MSExperiment() fh.load("feature_test.mzML", input_map) input_map.updateRanges() ff = FeatureFinder() ff.setLogType(LogType.CMD) # Run the feature finder name = "centroided" features = FeatureMap() seeds = FeatureMap() params = FeatureFinder().getParameters(name) ff.run(name, input_map, features, params, seeds) features.setUniqueIds() fh = FeatureXMLFile() fh.store("output.featureXML", features) print("Found", features.size(), "features")