Version Compatibility

Reference examples tested with: koinapy 0.0.5+, ms2pip 4.0+, deeplc 3.0+, pandas 2.2+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

DIA Spectral Libraries -- Query Parameters That Are Only as Good as Their Empirical Calibration

"Build a spectral library for my DIA search" -> Assemble a table of peptide query parameters (precursor m/z, top fragment m/z plus relative intensities, normalized RT, optional CCS), then calibrate the predicted RT/CCS to the actual gradient/instrument -- because a DIA library is not whole spectra and an uncalibrated prediction extracts every peak group at the wrong time.

• Python: koinapy.Koina(...).predict(df) for Prosit/AlphaPeptDeep/MS2PIP/UniSpec fragment intensities and iRT served from Koina
• Python: deeplc.DeepLC().calibrate_preds(); .make_preds() for RT prediction of any modification
• Python: ms2pip.predict_batch(psms, model='HCD') for local fragment-intensity prediction
• CLI: EncyclopeDIA for empirical chromatogram libraries; EasyPQP/FragPipe for DDA-based libraries