UniNovo: a universal tool for de novo peptide sequencing
peer-reviewed · Bioinformatics · 2013
| Date | 2013-08-15 |
| Type | peer-reviewed |
| Venue | Bioinformatics |
| Publisher | Oxford University Press (OUP) |
| Contribution | algorithm |
| DOI | 10.1093/bioinformatics/btt338 |
| Citations (OpenAlex) | 79 |
| Venue 2-year citedness | 5.93 |
Abstract
MOTIVATION: Mass spectrometry (MS) instruments and experimental protocols are rapidly advancing, but de novo peptide sequencing algorithms to analyze tandem mass (MS/MS) spectra are lagging behind. Although existing de novo sequencing tools perform well on certain types of spectra [e.g. Collision Induced Dissociation (CID) spectra of tryptic peptides], their performance often deteriorates on other types of spectra, such as Electron Transfer Dissociation (ETD), Higher-energy Collisional Dissociation (HCD) spectra or spectra of non-tryptic digests. Thus, rather than developing a new algorithm for each type of spectra, we develop a universal de novo sequencing algorithm called UniNovo that works well for all types of spectra or even for spectral pairs (e.g. CID/ETD spectral pairs). UniNovo uses an improved scoring function that captures the dependences between different ion types, where such dependencies are learned automatically using a modified offset frequency function. RESULTS: The performance of UniNovo is compared with PepNovo+, PEAKS and pNovo using various types of spectra. The results show that the performance of UniNovo is superior to other tools for ETD spectra and superior or comparable with others for CID and HCD spectra. UniNovo also estimates the probability that each reported reconstruction is correct, using simple statistics that are readily obtained from a small training dataset. We demonstrate that the estimation is accurate for all tested types of spectra (including CID, HCD, ETD, CID/ETD and HCD/ETD spectra of trypsin, LysC or AspN digested peptides). AVAILABILITY: UniNovo is implemented in JAVA and tested on Windows, Ubuntu and OS X machines. UniNovo is available at http://proteomics.ucsd.edu/Software/UniNovo.html along with the manual.
Methods and tools
- UniNovo: Universal de novo sequencing tool trained across fragmentation methods and instruments.
Cites (11)
- De Novo Sequencing and Homology Searching (2012) both
- ADEPTS: Advanced peptide de novo sequencing with a pair of tandem mass spectra (2010) both
- pNovo: De novo Peptide Sequencing and Identification Using HCD Spectra (2010) both
- Spectral Profiles, a Novel Representation of Tandem Mass Spectra and Their Applications for de Novo Peptide Sequencing and Identification (2009) both
- Spectral Dictionaries: Integrating de novo Peptide Sequencing with Database Search of Tandem Mass Spectra (2009) both
- Lookup Peaks: A Hybrid of de Novo Sequencing and Database Search for Protein Identification by Tandem Mass Spectrometry (2007) both
- Proteomics-Grade de Novo Sequencing Approach (2005) both
- PepNovo: de novo peptide sequencing via probabilistic network modeling (2005) both
- PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry (2003) crossref
- A Dynamic Programming Approach to De Novo Peptide Sequencing via Tandem Mass Spectrometry (2001) both
- De novo peptide sequencing via tandem mass spectrometry (1999) both
Cited by (17)
- Identification of Unknown Biological Toxin Proteins Using Mass Spectrometry: A Case Study on De Novo Sequencing of Ricin (2025) both
- De Novo Peptide Sequencing for Data-independent Acquisition (DIA) Using Deep Learning (2025) crossref
- PepGo: a deep learning and tree search-based model for de novo peptide sequencing (2025) crossref
- Accurate de novo peptide sequencing using fully convolutional neural networks (2023) both
- Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review (2023) crossref
- De novo sequencing of proteins by mass spectrometry (2020) both
- A potential golden age to come—current tools, recent use cases, and future avenues for de novo sequencing in proteomics (2018) crossref
- pSite: Amino Acid Confidence Evaluation for Quality Control of De Novo Peptide Sequencing and Modification Site Localization (2017) crossref
- De novo peptide sequencing by deep learning (2017) crossref
- Combining De Novo Peptide Sequencing Algorithms, A Synergistic Approach to Boost Both Identifications and Confidence in Bottom-up Proteomics (2017) crossref
- Comprehensive de Novo Peptide Sequencing from MS/MS Pairs Generated through Complementary Collision Induced Dissociation and 351 nm Ultraviolet Photodissociation (2017) both
- Evaluating de novo sequencing in proteomics: already an accurate alternative to database-driven peptide identification? (2017) crossref
- MRUniNovo: an efficient tool for de novo peptide sequencing utilizing the Hadoop distributed computing framework (2017) crossref
- Open-pNovo: De Novo Peptide Sequencing with Thousands of Protein Modifications (2017) crossref
- De novo peptide sequencing using CID and HCD spectra pairs (2016) crossref
- UVnovo: A de Novo Sequencing Algorithm Using Single Series of Fragment Ions via Chromophore Tagging and 351 nm Ultraviolet Photodissociation Mass Spectrometry (2016) both
- Novor: Real-Time Peptide de Novo Sequencing Software (2015) both