Evidence map›Paper›PMID 23599424›Full record

ArticleMolecular & cellular proteomics : MCP2013

The mzQuantML data standard for mass spectrometry-based quantitative studies in proteomics.

Mathias Walzer, Da Qi, Gerhard Mayer, Julian Uszkoreit, Martin Eisenacher, Timo Sachsenberg, Faviel F Gonzalez-Galarza, Jun Fan, Conrad Bessant, Eric W Deutsch and 6 more

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Software Options for the Analysis of MS-Proteomic Data.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  5. Article
  6. Proteomics Standards Initiative Extended FASTA Format.Journal of proteome research · 2019
    Article
  7. iProX: an integrated proteome resource.Nucleic acids research · 2019
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. A Golden Age for Working with Public Proteomics Data.Trends in biochemical sciences · 2017
    Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Review
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

16 authors.

Mathias WalzerQuantitative Biology Center and Department of Computer Science, Center for Bioinformatics, University of Tübingen, Sand 14, 72076 Tübingen, Germany.
Da Qi
Gerhard Mayer
Julian Uszkoreit
Martin Eisenacher
Timo Sachsenberg
Faviel F Gonzalez-Galarza
Jun Fan
Conrad Bessant
Eric W Deutsch
Florian Reisinger
Juan Antonio Vizcaíno
J Alberto Medina-Aunon
Juan Pablo Albar
Oliver Kohlbacher
Andrew R Jones

Funding

Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
Complete Human Peptide- and MRM-AtlasRC2HG005805 · NHGRI · INSTITUTE FOR SYSTEMS BIOLOGY · PI HOOD, LEROY E, MORITZ, ROBERT L · 2009 to 2010
$4.6M
Biotechnology and Biological Sciences Research Council BB/H024654/1Biotechnology and Biological Sciences Research Council BB/I000909/1Biotechnology and Biological Sciences Research Council BB/I00095X/1Biotechnology and Biological Sciences Research Council BB/I001131/1NHGRI NIH HHS HG005805NHGRI NIH HHS RC2 HG005805NIGMS NIH HHS GM087221NIGMS NIH HHS R01 GM087221Wellcome TrustWellcome Trust WT085949MA
6 · The paper itself

Abstract

The range of heterogeneous approaches available for quantifying protein abundance via mass spectrometry (MS)(1) leads to considerable challenges in modeling, archiving, exchanging, or submitting experimental data sets as supplemental material to journals. To date, there has been no widely accepted format for capturing the evidence trail of how quantitative analysis has been performed by software, for transferring data between software packages, or for submitting to public databases. In the context of the Proteomics Standards Initiative, we have developed the mzQuantML data standard. The standard can represent quantitative data about regions in two-dimensional retention time versus mass/charge space (called features), peptides, and proteins and protein groups (where there is ambiguity regarding peptide-to-protein inference), and it offers limited support for small molecule (metabolomic) data. The format has structures for representing replicate MS runs, grouping of replicates (for example, as study variables), and capturing the parameters used by software packages to arrive at these values. The format has the capability to reference other standards such as mzML and mzIdentML, and thus the evidence trail for the MS workflow as a whole can now be described. Several software implementations are available, and we encourage other bioinformatics groups to use mzQuantML as an input, internal, or output format for quantitative software and for structuring local repositories. All project resources are available in the public domain from the HUPO Proteomics Standards Initiative http://www.psidev.info/mzquantml.

Indexed as

Databases, ProteinMass SpectrometryModels, TheoreticalProteomicsSoftware

Identifiers

PMID23599424
PMCPMC3734589

What OpenQuestion holds

Textmetadata
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.