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

被引:14
作者
Baker, Erin S. [1 ]
Patti, Gary J. [2 ,3 ]
机构
[1] North Carolina State Univ, Dept Chem, Raleigh, NC 27695 USA
[2] Washington Univ, Dept Chem, St Louis, MO 63110 USA
[3] Washington Univ, Dept Med, St Louis, MO 63110 USA
关键词
Metabolomics; Informatics; ASMS Fall Workshop; Metabolism; UNTARGETED METABOLOMICS; SPECTROMETRY DATA; ANNOTATION; STANDARDS; PATHWAYS; SOFTWARE; FEATURES; METLIN; XCMS;
D O I
10.1007/s13361-019-02295-3
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:2031 / 2036
页数:6
相关论文
共 28 条
[1]  
[Anonymous], ANNOTATION LC ESI MS
[2]   Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics [J].
Blazenovic, Ivana ;
Kind, Tobias ;
Ji, Jian ;
Fiehn, Oliver .
METABOLITES, 2018, 8 (02)
[3]   RAMClust: A Novel Feature Clustering Method Enables Spectral-Matching-Based Annotation for Metabolomics Data [J].
Broeckling, C. D. ;
Afsar, F. A. ;
Neumann, S. ;
Ben-Hur, A. ;
Prenni, J. E. .
ANALYTICAL CHEMISTRY, 2014, 86 (14) :6812-6817
[4]   The MetaCyc database of metabolic pathways and enzymes [J].
Caspi, Ron ;
Billington, Richard ;
Fulcher, Carol A. ;
Keseler, Ingrid M. ;
Kothari, Anamika ;
Krummenacker, Markus ;
Latendresse, Mario ;
Midford, Peter E. ;
Ong, Quang ;
Ong, Wai Kit ;
Paley, Suzanne ;
Subhraveti, Pallavi ;
Karp, Peter D. .
NUCLEIC ACIDS RESEARCH, 2018, 46 (D1) :D633-D639
[5]   After the feature presentation: technologies bridging untargeted metabolomics and biology [J].
Cho, Kevin ;
Mahieu, Nathaniel G. ;
Johnson, Stephen L. ;
Patti, Gary J. .
CURRENT OPINION IN BIOTECHNOLOGY, 2014, 28 :143-148
[6]   Metabolite identification: are you sure? And how do your peers gauge your confidence? [J].
Creek, Darren J. ;
Dunn, Warwick B. ;
Fiehn, Oliver ;
Griffin, Julian L. ;
Hall, Robert D. ;
Lei, Zhentian ;
Mistrik, Robert ;
Neumann, Steffen ;
Schymanski, Emma L. ;
Sumner, Lloyd W. ;
Trengove, Robert ;
Wolfender, Jean-Luc .
METABOLOMICS, 2014, 10 (03) :350-353
[7]   Mass Spectral Feature List Optimizer (MS-FLO): A Tool To Minimize False Positive Peak Reports in Untargeted Liquid Chromatography-Mass Spectroscopy (LC-MS) Data Processing [J].
DeFelice, Brian C. ;
Mehta, Sajjan Singh ;
Samra, Stephanie ;
Cajka, Tomas ;
Wancewicz, Benjamin ;
Fahrmann, Johannes F. ;
Fiehn, Oliver .
ANALYTICAL CHEMISTRY, 2017, 89 (06) :3250-3255
[8]   Bioinformatics: The Next Frontier of Metabolomics [J].
Johnson, Caroline H. ;
Ivanisevic, Julijana ;
Benton, H. Paul ;
Siuzdak, Gary .
ANALYTICAL CHEMISTRY, 2015, 87 (01) :147-156
[9]  
Kale NS, 2016, CURRENT PROTOCOLS BI, V53, P1, DOI [10.1002/0471250953.bi1413s53, DOI 10.1002/0471250953.bi1413s53]
[10]   KEGG: new perspectives on genomes, pathways, diseases and drugs [J].
Kanehisa, Minoru ;
Furumichi, Miho ;
Tanabe, Mao ;
Sato, Yoko ;
Morishima, Kanae .
NUCLEIC ACIDS RESEARCH, 2017, 45 (D1) :D353-D361