Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing

This Zenodo record contains the dataset and model weights for "Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing". This repository contains the following files: For the human dataset by Wang et al.: train_val_test_split.csv containing the mapping of the correct peptide by MaxQuant to either train, validation or test set psms_train_val_test.csv containing the mapping of correct PSMs (scan number, raw file and correct peptide by MaxQuant) to either train, validation or test set updated_spectralis_test_out.csv as before containing Spectralis-EA predictions and scores on test set, as well as initial peptides and scores by Casanovo and Novor and now containing also correct peptides by MaxQuant and Spectralis-scores on the combination of Casanovo and Novor sequences (column named spectralis_score_onlyRescoring) spectralis_test_out_heart_analysis.csv subset of 20220822_spectralis_test_out.csv containing only PSMs for the tissue heart with the computation of precision and recall values spectralis_test_out_pointnovo_deepnovo.csv containing predictions by DeepNovo and PointNovo with original scores and Spectralis-score, as well as correct peptides by MaxQuant For the nine-species dataset by Tran et al.: spectralis_ninespecies_out.csv containing spectrum identifiers, correct peptides by PEAKSDB, predicted peptides by the different de novo sequencing tools as well as original scores and Spectralis-scores for the different PSMs.