Evidence map›Paper›PMID 24635752›Full record

ArticleJournal of proteome research2014

Systematic assessment of survey scan and MS2-based abundance strategies for label-free quantitative proteomics using high-resolution MS data.

Chengjian Tu, Jun Li, Quanhu Sheng, Ming Zhang, Jun Qu

Abstract read
In one paragraph

Article in Journal of proteome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Deep Learning Based MS2 Feature Detection for Data-Independent Shotgun Proteomics.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022
    Article
  6. Article
  7. Article
  8. Review
  9. Modeling Corticosteroid Pharmacogenomics and Proteomics in Rat Liver.The Journal of pharmacology and experimental therapeutics · 2018
    Article
  10. Article
  11. Article
  12. IonStar enables high-precision, low-missing-data proteomics quantification in large biological cohorts.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

5 authors.

Chengjian TuDepartment of Pharmaceutical Sciences, University at Buffalo, State University of New York , Buffalo, NY 14260, United States.
Jun Li
Quanhu Sheng
Ming Zhang
Jun Qu

Funding

Systems Biology of GlycosylationR01HL103411 · NHLBI · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI NEELAMEGHAM, SRIRAM · 2011 to 2025
$7.1M
Synergistic Pharmacologicjntervention for Prevention of ROP (SPIPROP STUDY)U54HD071594 · NICHD · SUNY DOWNSTATE MEDICAL CENTER · PI QU, JUN · 2011 to 2015
$3.6M
NHLBI NIH HHS HL103411NHLBI NIH HHS R01 HL103411NICHD NIH HHS U54 HD071594NICHD NIH HHS U54HD071594
6 · The paper itself

Abstract

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R(2) > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery.

Indexed as

AnimalsDatabases, ProteinHumansIonsProteinsProteomicsRatsReproducibility of ResultsSensitivity and SpecificityTandem Mass SpectrometryIonsProteins

Identifiers

PMID24635752
PMCPMC3993956

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.