Literature DB >> 31440979

Perspectives on Data Analysis in Metabolomics: Points of Agreement and Disagreement from the 2018 ASMS Fall Workshop.

Erin S Baker1, Gary J Patti2.   

Abstract

In November 2018, the American Society for Mass Spectrometry hosted the Annual Fall Workshop on informatic methods in metabolomics. The Workshop included sixteen lectures presented by twelve invited speakers. The focus of the talks was untargeted metabolomics performed with liquid chromatography/mass spectrometry. In this review, we highlight five recurring topics that were covered by multiple presenters: (i) data sharing, (ii) artifacts and contaminants, (iii) feature degeneracy, (iv) database organization, and (v) requirements for metabolite identification. Our objective here is to present viewpoints that were widely shared among participants, as well as those in which varying opinions were articulated. We note that most of the presenting speakers employed different data processing software, which underscores the diversity of informatic programs currently being used in metabolomics. We conclude with our thoughts on the potential role of reference datasets as a step towards standardizing data processing methods in metabolomics.

Entities:  

Keywords:  ASMS Fall Workshop; Informatics; Metabolism; Metabolomics

Mesh:

Year:  2019        PMID: 31440979      PMCID: PMC7310669          DOI: 10.1007/s13361-019-02295-3

Source DB:  PubMed          Journal:  J Am Soc Mass Spectrom        ISSN: 1044-0305            Impact factor:   3.109


  24 in total

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3.  Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.

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Authors:  Kevin Cho; Nathaniel G Mahieu; Stephen L Johnson; Gary J Patti
Journal:  Curr Opin Biotechnol       Date:  2014-05-06       Impact factor: 9.740

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

Authors:  Nathaniel G Mahieu; Jonathan L Spalding; Susan J Gelman; Gary J Patti
Journal:  Anal Chem       Date:  2016-08-31       Impact factor: 6.986

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Journal:  Metabolomics       Date:  2007-09       Impact factor: 4.290

8.  Credentialing features: a platform to benchmark and optimize untargeted metabolomic methods.

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Journal:  Anal Chem       Date:  2014-09-22       Impact factor: 6.986

9.  The MetaCyc database of metabolic pathways and enzymes.

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Review 10.  Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics.

Authors:  Ivana Blaženović; Tobias Kind; Jian Ji; Oliver Fiehn
Journal:  Metabolites       Date:  2018-05-10
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