Evidence map›Paper›PMID 25631240›Full record

ReviewProteomics. Clinical applications2015

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

Eric W Deutsch, Luis Mendoza, David Shteynberg, Joseph Slagel, Zhi Sun, Robert L Moritz

Abstract readReview
In one paragraph

Review in Proteomics. Clinical applications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 193 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
193citing papers in PubMed, 2 pooled it
–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

193 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Phosphorylation in theJournal of proteome research · 2024
    Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Journal of proteome research · 2025
    Article
  15. Article
  16. Shotgun Proteomics Protocol for Insects.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  17. Article
  18. Article
  19. Differential prolyl hydroxylation by six Physcomitrella prolyl-4 hydroxylases.Computational and structural biotechnology journal · 2024
    Article
  20. Article

133 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

6 authors.

Eric W DeutschInstitute for Systems Biology, Seattle, WA, USA.
Luis MendozaInstitute for Systems Biology, Seattle, WA, USA.
David ShteynbergInstitute for Systems Biology, Seattle, WA, USA.
Joseph SlagelInstitute for Systems Biology, Seattle, WA, USA.
Zhi SunInstitute for Systems Biology, Seattle, WA, USA.
Robert L MoritzInstitute for Systems Biology, Seattle, WA, USA.

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2006 to 2016
$30.6M
TrainingU54EB020406 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2014 to 2018
$12.5M
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
Medical Research Council 0923536NHGRI NIH HHS RC2 HG005805NIBIB NIH HHS U54 EB020406NIBIB NIH HHS U54EB020406NIGMS NIH HHS 2P50 GM076547NIGMS NIH HHS P50 GM076547NIGMS NIH HHS R01 GM087221
6 · The paper itself

Abstract

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features.

Indexed as

Statistics as TopicComputational BiologyHumansProteomeProteomicsReproducibility of ResultsSoftwareProteomeBioinformaticsMass spectrometry

Identifiers

PMID25631240
PMCPMC4506239

What OpenQuestion holds

Textmetadata
LicenceTDM
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.