Combining De Novo Peptide Sequencing Algorithms, A Synergistic Approach to Boost Both Identifications and Confidence in Bottom-up Proteomics
peer-reviewed · Journal of Proteome Research · 2017
| Date | 2017-06-14 |
| Type | peer-reviewed |
| Venue | Journal of Proteome Research |
| Publisher | ACS |
| Contribution | post-processor |
| DOI | 10.1021/acs.jproteome.7b00198 |
| Citations (OpenAlex) | 18 |
| Venue 2-year citedness | 3.48 |
Abstract
Complex mass spectrometry based proteomics data sets are mostly analyzed by protein database searches. While this approach performs considerably well for sequenced organisms, direct inference of peptide sequences from tandem mass spectra, i.e., de novo peptide sequencing, oftentimes is the only way to obtain information when protein databases are absent. However, available algorithms suffer from drawbacks such as lack of validation and often high rates of false positive hits (FP). Here we present a simple method of combining results from commonly available de novo peptide sequencing algorithms, which in conjunction with minor tweaks in data acquisition ensues lower empirical FDR compared to the analysis using single algorithms. Results were validated using state-of-the art database search algorithms as well specifically synthesized reference peptides. Thus, we could increase the number of PSMs meeting a stringent FDR of 5% more than 3-fold compared to the single best de novo sequencing algorithm alone, accounting for an average of 11 120 PSMs (combined) instead of 3476 PSMs (alone) in triplicate 2 h LC-MS runs of tryptic HeLa digestion.
Methods and tools
- DeNovo Synergy: Combining multiple de novo tools
Cites (11)
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Cited by (5)
- Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing (2024) semanticscholar
- Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly (2023) both
- Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing (2023) crossref
- Postnovo: Postprocessing Enables Accurate and FDR-Controlled de Novo Peptide Sequencing (2018) crossref
- A potential golden age to come—current tools, recent use cases, and future avenues for de novo sequencing in proteomics (2018) crossref