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Cited by 151Metabolomics and Mass Spectrometry StudiesAdvanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

A roadmap for the XCMS family of software solutions in metabolomics

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Mahieu, Nathaniel G, Genenbacher, Jessica Lloyd, Patti, Gary J·2016·Current Opinion in Chemical Biology
DOI 10.1016/j.cbpa.2015.11.009PMC PMC4831061
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Abstract

Global profiling of metabolites in biological samples by liquid chromatography/mass spectrometry results in datasets too large to evaluate manually. Fortunately, a variety of software programs are now available to automate the data analysis. Selection of the appropriate processing solution is dependent upon experimental design. Most metabolomic studies a decade ago had a relatively simple experimental design in which the intensities of compounds were compared between only two sample groups. More recently, however, increasingly sophisticated applications have been pursued. Examples include comparing compound intensities between multiple sample groups and unbiasedly tracking the fate of specific isotopic labels. The latter types of applications have necessitated the development of new software programs, which have introduced additional functionalities that facilitate data analysis. The objective of this review is to provide an overview of the freely available bioinformatic solutions that are either based upon or are compatible with the algorithms in XCMS, which we broadly refer to here as the 'XCMS family' of software. These include CAMERA, credentialing, Warpgroup, metaXCMS, X(13)CMS, and XCMS Online. Together, these informatic technologies can accommodate most cutting-edge metabolomic applications and offer unique advantages when compared to the original XCMS program.

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  • Metabolite identities were predicted from exact mass, retention time compared with authentic standards, and tandem mass spectra fragmentation pattern compared with in-house standards and online databases.

    “the identity predicted based on (i) the exact mass calculated from the mass per charge ratio; (ii) retention time compared to authentic standards, and (iii) the tandem mass spectra fragmentation pattern, compared to in-house standards, and online database 57,59,60 .”

    From APOE4-drives brain bioenergetic shifts independent of Alzheimer’s disease pathology (2026) · cites this paper as [60]

    The XCMS Online: Metabolomics on the Cloud section says uploaded MS and MS/MS data can be matched against the METLIN database using accurate mass and fragmentation patterns. It does not describe comparing retention times with authentic standards or fragmentation patterns with in-house standards, so those parts of the attributed method are unsupported. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 44

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Cited by

Sorted by citations

Authors
Mahieu, N. G., Genenbacher, J. L., & Patti, G. J.
Affiliations
Washington University in St. Louis (US)
Corresponding author
Patti, Gary J
ORCID
Venue
Current Opinion in Chemical Biology
Publisher
Elsevier BV
Published
2016-02
Volume
30
Pages
87-93
ISSN
1367-5931 (ISSN-L)
DOI
10.1016/j.cbpa.2015.11.009
PMC
PMC4831061
OpenAlex
W2196469775
Cited by
151
References
0
Citations by year
2026: 13 · 2025: 14 · 2024: 19 · 2023: 11 · 2022: 13 · 2021: 14 · 2020: 15 · 2019: 22 · 2018: 18 · 2017: 10 · 2016: 2
FWCI
0.97
Type
journal article
Language
en
Open access
Licence
Locations
  • Current Opinion in Chemical Biology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institutes of Health (R01 ES022181, R21 CA191097)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
XCMS, camera, credentialing, multiple group comparison, bioinformatics software
MeSH terms
Software, Artifacts, Internet, Metabolomics, Molecular Sequence Annotation

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