Evidence map›Paper›PMID 30315456›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2019

A Protocol to Compare Methods for Untargeted Metabolomics.

Lingjue Wang, Fuad J Naser, Jonathan L Spalding, Gary J Patti

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. An optimization method for untargeted MS-based isotopic tracing investigations of metabolism.Metabolomics : Official journal of the Metabolomic Society · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Chemical Discovery in the Era of Metabolomics.Journal of the American Chemical Society · 2020
    Review
  15. An LC-QToF MS based method for untargeted metabolomics of human fecal samples.Metabolomics : Official journal of the Metabolomic Society · 2020
    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

4 authors.

Lingjue WangDepartment of Chemistry, Washington University, St. Louis, MO, USA.
Fuad J NaserDepartment of Chemistry, Washington University, St. Louis, MO, USA.
Jonathan L SpaldingDepartment of Chemistry, Washington University, St. Louis, MO, USA.
Gary J PattiDepartment of Chemistry, Washington University, St. Louis, MO, USA. gjpattij@wustl.edu.

Funding

TRAINING PROGRAM IN CELLULAR AND MOLECULAR BIOLOGYT32GM007067 · NIGMS · WASHINGTON UNIVERSITY · PI TRUE-KROB, HEATHER L · 1985 to 2020
$20.4M
Training Program in Cellular and Molecular BiologyT32GM139774 · NIGMS · WASHINGTON UNIVERSITY · PI HEATHER L TRUE-KROB · 2021 to 2026
$6.7M
Developing Metabolomic Technologies to Advance Environmental Exposure AnalysisR35ES028365 · NIEHS · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2017 to 2024
$5.9M
A COMPREHENSIVE RESOURCE FOR HIGH-THROUGHPUT PROFILING OF WORM AND ZEBRAFISH METABOLOMESR24OD024624 · OD · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2018 to 2021
$4.0M
A Comprehensive Platform for High-Throughput Profiling of the Human Reference MetabolomeU01CA235482 · NCI · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2018 to 2021
$1.8M
CELL-SPECIFIC ISOTOPE LABELING TO TRACK INTERCELLULAR METABOLITE EXCHANGE IN CANCERR21CA191097 · NCI · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2015 to 2017
$663k
NCATS NIH HHS L30 TR000589NCI NIH HHS R21 CA191097NCI NIH HHS U01 CA235482NIEHS NIH HHS R35 ES028365NIGMS NIH HHS T32 GM007067NIGMS NIH HHS T32 GM139774NIH HHS R24 OD024624
6 · The paper itself

Abstract

There are thousands of published methods for profiling metabolites with liquid chromatography/mass spectrometry (LC/MS). While many have been evaluated and optimized for a small number of select metabolites, very few have been assessed on the basis of global metabolite coverage. Thus, when performing untargeted metabolomics, researchers often question which combination of extraction techniques, chromatographic separations, and mass spectrometers is best for global profiling. Method comparisons are complicated because thousands of LC/MS signals (so-called features) in a typical untargeted metabolomic experiment cannot be readily identified with current resources. It is therefore challenging to distinguish methods that increase signal number due to improved metabolite coverage from methods that increase signal number due to contamination and artifacts. Here, we present the credentialing protocol to remove the latter from untargeted metabolomic datasets without having to identify metabolite structures. This protocol can be used to compare or optimize methods pertaining to any step of the untargeted metabolomic workflow (e.g., extraction, chromatography, mass spectrometer, informatic software, etc.).

Indexed as

Data AnalysisChromatography, High Pressure LiquidDatasets as TopicMetabolomicsSoftwareTandem Mass SpectrometryCredentialingLiquid chromatographyMass spectrometryMetabolismMetabolite profilingUntargeted metabolomics

Identifiers

PMID30315456
PMCPMC6482454

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.