ArticleJournal of proteome research2015
Tandem Mass Spectrum Identification via Cascaded Search.
Article in Journal of proteome research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- PTMs_Closed_Search: Multiple Post-Translational Modification Closed Search Using Reduced Search Space and Transferred FDR.Proteomes · 2026Article
- Comparative performance of Scribe and database search engines in metaproteomic profiling of a ground-truth microbiome dataset.Journal of proteomics · 2026Article
- Sequence-to-sequence translation from mass spectra to peptides with a transformer model.Nature communications · 2024Article
- A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease.mSphere · 2024Article
- The Association of Biomolecular Resource Facilities Proteome Informatics Research Group Study on Metaproteomics (iPRG-2020).Journal of biomolecular techniques : JBT · 2023Article
- Accelerating open modification spectral library searching on tensor core in high-dimensional space.Bioinformatics (Oxford, England) · 2023Article
- The Crux Toolkit for Analysis of Bottom-Up Tandem Mass Spectrometry Proteomics Data.Journal of proteome research · 2023Article
- Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows.Nature communications · 2021Article
- Accurately Assigning Peptides to Spectra When Only a Subset of Peptides Are Relevant.Journal of proteome research · 2021Article
- Enhancing Open Modification Searches via a Combined Approach Facilitated by Ursgal.Journal of proteome research · 2021Article
- Focus on the spectra that matter by clustering of quantification data in shotgun proteomics.Nature communications · 2020Article
- The Archaeal Proteome Project advances knowledge about archaeal cell biology through comprehensive proteomics.Nature communications · 2020Article
- Extremely Fast and Accurate Open Modification Spectral Library Searching of High-Resolution Mass Spectra Using Feature Hashing and Graphics Processing Units.Journal of proteome research · 2019Article
- A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation.Molecular & cellular proteomics : MCP · 2019Article
- A high-speed search engine pLink 2 with systematic evaluation for proteome-scale identification of cross-linked peptides.Nature communications · 2019Article
- Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing.Journal of proteome research · 2019Review
- Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing.Journal of proteome research · 2018Article
- Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework.Proteomes · 2018Article
- Progressive calibration and averaging for tandem mass spectrometry statistical confidence estimation: Why settle for a single decoy?Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- ) · 2017Article
- Critical decisions in metaproteomics: achieving high confidence protein annotations in a sea of unknowns.The ISME journal · 2017Article
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Authors and funding
3 authors.
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Abstract
Accurate assignment of peptide sequences to observed fragmentation spectra is hindered by the large number of hypotheses that must be considered for each observed spectrum. A high score assigned to a particular peptide-spectrum match (PSM) may not end up being statistically significant after multiple testing correction. Researchers can mitigate this problem by controlling the hypothesis space in various ways: considering only peptides resulting from enzymatic cleavages, ignoring possible post-translational modifications or single nucleotide variants, etc. However, these strategies sacrifice identifications of spectra generated by rarer types of peptides. In this work, we introduce a statistical testing framework, cascade search, that directly addresses this problem. The method requires that the user specify a priori a statistical confidence threshold as well as a series of peptide databases. For instance, such a cascade of databases could include fully tryptic, semitryptic, and nonenzymatic peptides or peptides with increasing numbers of modifications. Cascaded search then gradually expands the list of candidate peptides from more likely peptides toward rare peptides, sequestering at each stage any spectrum that is identified with a specified statistical confidence. We compare cascade search to a standard procedure that lumps all of the peptides into a single database, as well as to a previously described group FDR procedure that computes the FDR separately within each database. We demonstrate, using simulated and real data, that cascade search identifies more spectra at a fixed FDR threshold than with either the ungrouped or grouped approach. Cascade search thus provides a general method for maximizing the number of identified spectra in a statistically rigorous fashion.
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