Evidence map›Paper›PMID 39321875›Full record

ArticleMolecular & cellular proteomics : MCP2024

NovoBoard: A Comprehensive Framework for Evaluating the False Discovery Rate and Accuracy of De Novo Peptide Sequencing.

Ngoc Hieu Tran, Rui Qiao, Zeping Mao, Shengying Pan, Qing Zhang, Wenting Li, Lei Xin, Ming Li, Baozhen Shan

Erratum issuedAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Ngoc Hieu TranBioinformatics Solutions Inc, Waterloo, Ontario, Canada.
Rui QiaoBioinformatics Solutions Inc, Waterloo, Ontario, Canada.
Zeping MaoBioinformatics Solutions Inc, Waterloo, Ontario, Canada; David R. Cheriton School of Computer Science, University of Waterloo, Ontario, Canada.
Shengying PanBioinformatics Solutions Inc, Waterloo, Ontario, Canada.
Qing ZhangBioinformatics Solutions Inc, Waterloo, Ontario, Canada.
Wenting LiBioinformatics Solutions Inc, Waterloo, Ontario, Canada.
Lei XinBioinformatics Solutions Inc, Waterloo, Ontario, Canada. Electronic address: lxin@bioinfor.com.
Ming LiDavid R. Cheriton School of Computer Science, University of Waterloo, Ontario, Canada. Electronic address: mli@uwaterloo.ca.
Baozhen ShanBioinformatics Solutions Inc, Waterloo, Ontario, Canada. Electronic address: bshan@bioinfor.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

De novo peptide sequencing is one of the most fundamental research areas in mass spectrometry-based proteomics. Many methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) of de novo peptide-spectrum matches. Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide-sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species) and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide-sequencing methods on target-decoy spectra and to estimate and validate their FDRs. Our FDR estimation provides valuable information to assess the reliability of new peptides identified by de novo sequencing tools, especially when no ground-truth information is available to evaluate their accuracy. The FDR estimation can also be used to evaluate the capability of de novo peptide sequencing tools to distinguish between de novo peptide-spectrum matches and random matches. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide-sequencing methods and how their performances depend on specific applications and the types of data.

Indexed as

PeptidesProteomicsSequence Analysis, ProteinAnimalsDatabases, ProteinHumansReproducibility of ResultsSoftwarePeptidesdeep learningde novo peptide sequencingfalse discovery ratemass spectrometryneural network

Identifiers

PMID39321875
PMCPMC11532909

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.