Version: 2.1
Passatutto is a framework for converting metabolomics identification scores to posterior error probability.
Passatutto enables the assessment of confidence in a match for metabolomics mass spectral library search. The tool allows for either an empirical Bayes or a target-decoy approach to be used. Different methods to construct the decoy database can be used, all of them avoiding to construct “decoy metabolite structures”. In addition, passatutto can be used for noise-filtering reference spectra based on fragmentation trees.
- FDR and PEP scores for metabolomics identification.
- Metabolomics / Untargeted
- MS / LC-MS
- MS / GC-MS
- Kerstin Scheubert
- Franziska Hufsky
- Daniel Petras
- Mingxun Wang
- Louis-Felix Nothias
- Kai Dührkop
- Nuno Bandeira
- Pieter C Dorrestein
- Sebastian Böcker
- Christoph Ruttkies (IPB-Halle)
- Payam Emami (UU)
- Kerstin Scheubert, Franziska Hufsky, Daniel Petras, Mingxun Wang, Louis-Felix Nothias, Kai Dührkop, Nuno Bandeira, Pieter C Dorrestein, Sebastian Böcker. Significance estimation enabling large scale untargeted metabolomics annotations. Nature Communications, 2017. 8(1494) DOI: 10.1038/s41467-017-01318-5