Probabilistic de novo peptide sequencing with doubly charged ions

Sequencing of peptides by tandem mass spectrometry has matured to the key technology for proteomics. Noise in the measurement process strongly favors statistical models like NovoHMM, a recently published generative approach based on factorial hidden Markov models [1,2]. We extend this hidden Markov model to include information of doubly charged ions since the original model can only cope with singly charged ions. This modification requires a refined discretization of the mass scale and, thereby, it increases its sensitivity and recall performance on a number of datasets to compare favorably with alternative approaches for mass spectra interpretation.