oktoberfest.pr.Predictor.predict_at_once

Predictor.predict_at_once(data, xl=False, **kwargs)

Retrieve and return predictions in one go.

This function takes a Spectra object containing information about PSMs and predicts peptide properties. The configuration of Koina is set using the kwargs. See the Koina function for details. TODO, link this properly.

Parameters:

  • data (Spectra) – Spectra containing the data for the prediction.

  • xl (bool) – crosslinked or linear peptide

  • kwargs – Additional parameters that are forwarded to Koina

Return type:

tuple[dict[str, ndarray], dict[str, ndarray]] | dict[str, ndarray]

Returns:

a dictionary with targets (keys) and predictions (values)

Example:

>>> from oktoberfest import predict as pr
>>> import pandas as pd
>>> # Required columns: MODIFIED_SEQUENCE, COLLISION_ENERGY, PRECURSOR_CHARGE and FRAGMENTATION
>>> meta_df = pd.DataFrame({"MODIFIED_SEQUENCE": ["AAAC[UNIMOD:4]RFVQ","RM[UNIMOD:35]PC[UNIMOD:4]HKPYL"],
>>>                         "COLLISION_ENERGY": [30,35],
>>>                         "PRECURSOR_CHARGE": [1,2],
>>>                         "FRAGMENTATION": ["HCD","HCD"]})
>>> var = Spectra._gen_vars_df()
>>> library = Spectra(obs=meta_df, var=var)
>>> intensity_predictor = pr.Predictor.from_koina(
>>>                         model_name="Prosit_2020_intensity_HCD",
>>>                         server_url="koina.wilhelmlab.org:443",
>>>                         ssl=True)
>>> predictions = intensity_predictor.predict_at_once(data=library)
>>> print(predictions)