ArticleJournal of proteome research2021
Accurately Assigning Peptides to Spectra When Only a Subset of Peptides Are Relevant.
Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 26 citations in OpenAlex.
- ImmunoPepper: extracting personalized peptides from complex splicing graphs.Bioinformatics (Oxford, England) · 2026Article
- Deep Learning Enhances Precision of Citrullination Identification in Human and Plant Tissue Proteomes.Molecular & cellular proteomics : MCP · 2025Article
- Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry.ACS measurement science au · 2024Review
- Article
- Improving Peptide-Level Mass Spectrometry Analysis via Double Competition.Journal of proteome research · 2022Article
- An analysis of proteogenomics and how and when transcriptome-informed reduction of protein databases can enhance eukaryotic proteomics.Genome biology · 2022Article
- Building Spectral Libraries from Narrow-Window Data-Independent Acquisition Mass Spectrometry Data.Journal of proteome research · 2022Article
- Considerations for constructing a protein sequence database for metaproteomics.Computational and structural biotechnology journal · 2022Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
The standard proteomics database search strategy involves searching spectra against a peptide database and estimating the false discovery rate (FDR) of the resulting set of peptide-spectrum matches. One assumption of this protocol is that all the peptides in the database are relevant to the hypothesis being investigated. However, in settings where researchers are interested in a subset of peptides, alternative search and FDR control strategies are needed. Recently, two methods were proposed to address this problem: subset-search and all-sub. We show that both methods fail to control the FDR. For subset-search, this failure is due to the presence of "neighbor" peptides, which are defined as irrelevant peptides with a similar precursor mass and fragmentation spectrum as a relevant peptide. Not considering neighbors compromises the FDR estimate because a spectrum generated by an irrelevant peptide can incorrectly match well to a relevant peptide. Therefore, we have developed a new method, "subset-neighbor search" (SNS), that accounts for neighbor peptides. We show evidence that SNS controls the FDR when neighbors are present and that SNS outperforms group-FDR, the only other method that appears to control the FDR relative to a subset of relevant peptides.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.