Evidence map›Paper›PMID 41713790›Full record

ArticleMolecular & cellular proteomics : MCP2026

pmultiqc: An Open-Source, Lightweight, and Metadata-Oriented QC Reporting Library for MS Proteomics.

Qi-Xuan Yue, Chengxin Dai, Selvakumar Kamatchinathan, Chakradhar Bandla, Henry Webel, Asier Larrea, Wout Bittremieux, Julian Uszkoreit, Tom David Müller, Jinqiu Xiao and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular & cellular proteomics : MCP, 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
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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

19 authors.

Qi-Xuan YueChongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China.
Chengxin DaiState Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Life Omics, Beijing, China.
Selvakumar KamatchinathanEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
Chakradhar BandlaEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
Henry WebelThe Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark.
Asier LarreaEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK; Faculty of Science and Technology, Department of Biochemistry and Molecular Biology, University of the Basque Country (UPV/EHU), Bilbao, Spain.
Wout BittremieuxDepartment of Computer Science, University of Antwerp, Antwerp, Belgium.
Julian UszkoreitMedical Faculty, Medical Bioinformatics, Ruhr University Bochum, Bochum, Germany; Core Unit Bioinformatics - CUBiMed.RUB, Medical Faculty, Ruhr University Bochum, Bochum, Germany.
Tom David MüllerDepartment of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen, Germany; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.
Jinqiu XiaoComputational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany.
Juergen CoxComputational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany.
Fengchao YuDepartment of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
Philip EwelsEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
Vadim DemichevQuantitative Proteomics Laboratory, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Oliver KohlbacherDepartment of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen, Germany; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany; Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany.
Timo SachsenbergDepartment of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen, Germany; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.
Chris BielowBioinformatics Solution Center, Institute of Computer Science, Freie Universität Berlin, Berlin, Germany.
Mingze BaiChongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China. Electronic address: baimz@cqupt.edu.cn.
Yasset Perez-RiverolEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK. Electronic address: yperez@ebi.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing scale and complexity of proteomics data demand robust, scalable, and interpretable quality control (QC) frameworks to ensure data reliability and reproducibility. Here, we present pmultiqc, an open-source Python package that standardizes and generates web-based QC reports across multiple proteomics data analysis platforms. Built on top of the widely adopted MultiQC framework, pmultiqc offers specialized modules tailored to mass spectrometry workflows, with full initial support for quantms, DIA-NN, MaxQuant/MaxDIA, FragPipe, and mzIdentML/mzML-based pipelines. The package computes a wide range of QC metrics, including raw intensity distributions, identification rates, retention time consistency, and missing value patterns, and presents them in interactive, publication-ready reports. By leveraging sample metadata in the Sample and Data Relationship Format format, pmultiqc enables metadata-aware QC and introduces, for the first time in proteomics, QC reports and metrics guided by standardized sample metadata. Its modular architecture allows easy extension to new workflows and formats. Alongside comprehensive documentation and examples for running pmultiqc locally or integrated into existing workflows, we offer a cloud-based service that enables users to generate QC reports from their own data or public PRIDE datasets.

Indexed as

Mass SpectrometryMetadataProteomicsSoftwareInternetQuality ControlReproducibility of ResultsWorkflowDIAFAIRlarge-scale data analysisquality controlreproducibilitySingle cell

Identifiers

PMID41713790
PMCPMC13234735

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.