Evidence map›Paper›PMID 27513885›Full record

ArticleAnalytical chemistry2016

Defining and Detecting Complex Peak Relationships in Mass Spectral Data: The Mz.unity Algorithm.

Nathaniel G Mahieu, Jonathan L Spalding, Susan J Gelman, Gary J Patti

Abstract read
In one paragraph

Article in Analytical chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing 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.

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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Assessing the metabolomics "dark matter" by a detectable khipu model.Metabolomics : Official journal of the Metabolomic Society · 2026
    Article
  5. Review
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  8. Metabolomics Data Processing Using the Asari Toolkit.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Metabolic rewiring of isoniazid sensitivity inProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Annotation of Metabolites in Stable Isotope Tracing Untargeted Metabolomics via Khipu-web.Journal of the American Society for Mass Spectrometry · 2024
    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

4 authors.

Nathaniel G MahieuDepartment of Chemistry, Washington University , St. Louis, Missouri 63130, United States .
Jonathan L SpaldingDepartment of Chemistry, Washington University , St. Louis, Missouri 63130, United States .
Susan J GelmanDepartment of Chemistry, Washington University , St. Louis, Missouri 63130, United States .
Gary J PattiDepartment of Chemistry, Washington University , St. Louis, Missouri 63130, United States .

Funding

DEVELOPING THE UNTARGETED METABOLOMIC WORKFLOW FOR HIGH-THROUGHPUT ANALYSESR01ES022181 · NIEHS · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2012 to 2016
$1.8M
CELL-SPECIFIC ISOTOPE LABELING TO TRACK INTERCELLULAR METABOLITE EXCHANGE IN CANCERR21CA191097 · NCI · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2015 to 2017
$663k
NCI NIH HHS R21 CA191097NIEHS NIH HHS R01 ES022181
6 · The paper itself

Abstract

Analysis of a single analyte by mass spectrometry can result in the detection of more than 100 degenerate peaks. These degenerate peaks complicate spectral interpretation and are challenging to annotate. In mass spectrometry-based metabolomics, this degeneracy leads to inflated false discovery rates, data sets containing an order of magnitude more features than analytes, and an inefficient use of resources during data analysis. Although software has been introduced to annotate spectral degeneracy, current approaches are unable to represent several important classes of peak relationships. These include heterodimers and higher complex adducts, distal fragments, relationships between peaks in different polarities, and complex adducts between features and background peaks. Here we outline sources of peak degeneracy in mass spectra that are not annotated by current approaches and introduce a software package called mz.unity to detect these relationships in accurate mass data. Using mz.unity, we find that data sets contain many more complex relationships than we anticipated. Examples include the adduct of glutamate and nicotinamide adenine dinucleotide (NAD), fragments of NAD detected in the same or opposite polarities, and the adduct of glutamate and a background peak. Further, the complex relationships we identify show that several assumptions commonly made when interpreting mass spectral degeneracy do not hold in general. These contributions provide new tools and insight to aid in the annotation of complex spectral relationships and provide a foundation for improved data set identification. Mz.unity is an R package and is freely available at https://github.com/nathaniel-mahieu/mz.unity as well as our laboratory Web site http://pattilab.wustl.edu/software/ .

Indexed as

SoftwareAlgorithmsGlutamic AcidMass SpectrometryMetabolomicsNADGlutamic AcidNAD

Identifiers

PMID27513885
PMCPMC6427821

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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.