Evidence map›Paper›PMID 41771895›Full record

ArticleNature communications2026

Analysis of isobaric quantitative proteomic data using TMT-Integrator and FragPipe computational platform.

Hui-Yin Chang, Yamei Deng, Ruohong Li, Dmitry Avtonomov, Bo Wen, Sarah E Haynes, Felipe da Veiga Leprevost, Bing Zhang, Fengchao Yu, Alexey I Nesvizhskii

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Hui-Yin Chang *Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
Yamei Deng *Department of Pathology, University of Michigan, Ann Arbor, MI, USA.ORCID http://orcid.org/0000-0002-3680-5930
Ruohong LiDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
Dmitry AvtonomovDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
Bo WenLester and Sue Smith Breast Center, Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA.ORCID http://orcid.org/0000-0003-2261-3150
Sarah E HaynesDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.ORCID http://orcid.org/0000-0003-3225-1691
Felipe da Veiga LeprevostDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
Bing ZhangLester and Sue Smith Breast Center, Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA.ORCID http://orcid.org/0000-0001-8676-2425
Fengchao YuDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA. yufe@umich.edu.ORCID http://orcid.org/0000-0002-7695-3698
Alexey I NesvizhskiiDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA. nesvi@med.umich.edu.ORCID http://orcid.org/0000-0002-2806-7819

Funding

COMPUTATIONAL TOOLS FOR MASS SPECTROMETRY-BASED INTERACTOME DATAR01GM094231 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Alexey I Nesvizhskii · 2010 to 2026
$5.4M
Michigan Compound Identification Development Cores (MCIDC)U2CES030164 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI EVANS, CHARLES ROBERT, NESVIZHSKII, ALEXEY I · 2018 to 2021
$4.1M
Ministry of Science and Technology, Taiwan (Ministry of Science and Technology of Taiwan) MOST-110-2320-B-008-001-MY2NIGMS NIH HHS R01 GM094231U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01-GM-094231U.S. Department of Health & Human Services | National Institutes of Health (NIH) U2CES030164
6 · The paper itself

Abstract

Isobaric mass tags, such as isobaric tags for relative and absolute quantitation (iTRAQ) and tandem mass tag (TMT), are widely utilized for peptide and protein quantification in multiplex quantitative proteomics. We present TMT-Integrator, a bioinformatics tool for processing quantitation results from TMT and iTRAQ experiments, offering integrative reports at the gene, protein, peptide, and post-translational modification site levels. We demonstrate the versatility of TMT-Integrator using five publicly available TMT datasets: clear cell renal cell carcinoma (ccRCC) whole proteome and phosphoproteome datasets from the Clinical Proteomic Tumor Analysis Consortium, an E. coli dataset with 13 spike-in proteins, and two human cell lysate datasets showcasing the latest advances with the Thermo Orbitrap Astral mass spectrometer and TMTpro 35-plex reagents. Integrated into the widely used FragPipe computational platform ( https://fragpipe.nesvilab.org/ ), TMT-Integrator is a core component of TMT and iTRAQ data analysis workflows. We evaluated the performance of FragPipe coupled with TMT-Integrator analysis pipeline against MaxQuant and Proteome Discoverer with multiple benchmarks, facilitated by the bioinformatics tool OmicsEV. Our results show that FragPipe coupled with TMT-Integrator quantifies more proteins in the E. coli and ccRCC whole proteome datasets, quantifies more phosphorylated sites in the ccRCC phosphoproteome dataset, and overall delivers more robust quantification performance compared to other tools.

Indexed as

Computational BiologyProteomeProteomicsCarcinoma, Renal CellEscherichia coliHumansKidney NeoplasmsProtein Processing, Post-TranslationalSoftwareTandem Mass SpectrometryProteome

Identifiers

PMID41771895
PMCPMC13136390

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.