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MS2Query

Description

For feature annotation, FERMO accepts results created by MS2Query, a machine-learning based annotation algorithm. MS2Query comes with its own spectral library derived from the GNPS library and can do exact and/or analog matching.

For compatibility with FERMO, the MS2Query results file must come with a column feature_id or id matching the peaktable feature IDs (default since MS2Query >= v1.5.3)

For more information on the algorithmm see the MS2Query Documentation.

Parameters

Key Possible Values Default
filepath (the filepath) N/A
score_cutoff 0.0-1.0 0.7

Explanation

  • score_cutoff: minimum score in ms2query_model_prediction to consider a match to be valid. Matches with a score lower than score_cutoff are not considered for molecular feature annotation.