Evidence map›Paper›PMID 27572102›Full record

ArticleJournal of the American Society for Mass Spectrometry2016

Fast and Accurate Protein False Discovery Rates on Large-Scale Proteomics Data Sets with Percolator 3.0.

Matthew The, Michael J MacCoss, William S Noble, Lukas Käll

Abstract read
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 236 papers.

0numbers the graph read from it
0cells of the map it votes in
236citing 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

236 citing papers in PubMed.

  1. iScience · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

176 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Matthew TheScience for Life Laboratory, School of Biotechnology, KTH - Royal Institute of Technology, Box 1031, 17121, Solna, Sweden.
Michael J MacCossDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, 98195, USA.
William S NobleDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, 98195, USA.
Lukas KällScience for Life Laboratory, School of Biotechnology, KTH - Royal Institute of Technology, Box 1031, 17121, Solna, Sweden. lukas.kall@scilifelab.se.

Funding

TrainingP41GM103533 · NIGMS · UNIVERSITY OF WASHINGTON · PI MACCOSS, MICHAEL · 2012 to 2021
$20.7M
Systematic and Comprehensive Sampling of Peptides in Mixtures by Tandem Mass SpectrometryR21CA192983 · NCI · UNIVERSITY OF WASHINGTON · PI MACCOSS, MICHAEL · 2015 to 2017
$648k
NCI NIH HHS R21 CA192983NIGMS NIH HHS P41 GM103533
6 · The paper itself

Abstract

Percolator is a widely used software tool that increases yield in shotgun proteomics experiments and assigns reliable statistical confidence measures, such as q values and posterior error probabilities, to peptides and peptide-spectrum matches (PSMs) from such experiments. Percolator's processing speed has been sufficient for typical data sets consisting of hundreds of thousands of PSMs. With our new scalable approach, we can now also analyze millions of PSMs in a matter of minutes on a commodity computer. Furthermore, with the increasing awareness for the need for reliable statistics on the protein level, we compared several easy-to-understand protein inference methods and implemented the best-performing method-grouping proteins by their corresponding sets of theoretical peptides and then considering only the best-scoring peptide for each protein-in the Percolator package. We used Percolator 3.0 to analyze the data from a recent study of the draft human proteome containing 25 million spectra (PM:24870542). The source code and Ubuntu, Windows, MacOS, and Fedora binary packages are available from http://percolator.ms/ under an Apache 2.0 license. Graphical Abstract ᅟ.

Indexed as

Databases, ProteinProteomicsSoftwareAlgorithmsHumansPeptidesTandem Mass SpectrometryPeptidesData processing and analysisLarge scale studiesMass spectrometry - LC-MS/MSProtein inferenceStatistical analysis

Identifiers

PMID27572102
PMCPMC5059416

What OpenQuestion holds

Textmetadata
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.