Evidence map›Paper›PMID 38693118›Full record

ArticleNature communications2024

MetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics.

Zhiqiang Pang, Lei Xu, Charles Viau, Yao Lu, Reza Salavati, Niladri Basu, Jianguo Xia

Registry-linked trialAbstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07232550 (Biomarkers and Respiratory Omics as New CHildren Opportunities - Study of Clinical Outcomes and Predictivity Evaluation - a Multi-cohort, Multi-center Study), which is not on this map. Cited by 149 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
149citing papers in PubMed, 1 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.

NCT07232550 recruitingnot on this mapstarted 2026, after this paper: background citation

Biomarkers and Respiratory Omics as New CHildren Opportunities - Study of Clinical Outcomes and Predictivity Evaluation - a Multi-cohort, Multi-center Study

TypeobservationalSponsorMedical University of WarsawRan2026 to 2035Enrolled160ConditionsAsthma in Children, Protracted Bacterial Bronchitis, Chronic CoughArmsfiberoptic bronchoscopy, blood sample collection, Respiratory functional tests, Sputum culture
3 · Its place in the literature

Who cites it

149 citing papers in PubMed, 1 synthesis or guideline pooled it.

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89 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

7 authors.

Zhiqiang PangFaculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
Lei XuFaculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
Charles ViauFaculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
Yao LuDepartment of Microbiology and Immunology, McGill University, Montreal, QC, Canada.
Reza SalavatiFaculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
Niladri BasuFaculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
Jianguo XiaFaculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada. jeff.xia@mcgill.ca.ORCID http://orcid.org/0000-0003-2040-2624

Funding

Mummichog 3, aligning mass spectrometry data to biological networks - Neutral LossU01CA235493 · NCI · JACKSON LABORATORY · PI LI, SHUZHAO, SIUZDAK, GARY E · 2018 to 2021
$2.0M
NCI NIH HHS U01 CA235493
6 · The paper itself

Abstract

The wide applications of liquid chromatography - mass spectrometry (LC-MS) in untargeted metabolomics demand an easy-to-use, comprehensive computational workflow to support efficient and reproducible data analysis. However, current tools were primarily developed to perform specific tasks in LC-MS based metabolomics data analysis. Here we introduce MetaboAnalystR 4.0 as a streamlined pipeline covering raw spectra processing, compound identification, statistical analysis, and functional interpretation. The key features of MetaboAnalystR 4.0 includes an auto-optimized feature detection and quantification algorithm for LC-MS1 spectra processing, efficient MS2 spectra deconvolution and compound identification for data-dependent or data-independent acquisition, and more accurate functional interpretation through integrated spectral annotation. Comprehensive validation studies using LC-MS1 and MS2 spectra obtained from standards mixtures, dilution series and clinical metabolomics samples have shown its excellent performance across a wide range of common tasks such as peak picking, spectral deconvolution, and compound identification with good computing efficiency. Together with its existing statistical analysis utilities, MetaboAnalystR 4.0 represents a significant step toward a unified, end-to-end workflow for LC-MS based global metabolomics in the open-source R environment.

Indexed as

Mass SpectrometryMetabolomicsWorkflowAlgorithmsChromatography, LiquidLiquid Chromatography-Mass SpectrometrySoftware

Identifiers

PMID38693118
PMCPMC11063062

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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.