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([1])
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")
FeatureFinderMetabo
, it was like a year ago so I can not recall the details right now, but you can see the entire thing here: github.com/saezlab/lipyd/blob/master/src/lipyd/msproc.py If you will be still having issues, maybe in the weekend I can check it again. $\endgroup$