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Sökning: id:"swepub:oai:DiVA.org:oru-113749" > Reproducible mass s...

Reproducible mass spectrometry data processing and compound annotation in MZmine 3

Heuckeroth, Steffen (författare)
University of Münster, Münster, Germany
Damiani, Tito (författare)
Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
Smirnov, Aleksandr (författare)
University of North Carolina at Charlotte, Charlotte, NC, USA
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Mokshyna, Olena (författare)
Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
Brungs, Corinna (författare)
Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
Korf, Ansgar (författare)
Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
Smith, Joshua David (författare)
Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic; First Faculty of Medicine, Charles University, Prague, Czech Republic
Stincone, Paolo (författare)
University of Tuebingen, Tuebingen, Germany
Dreolin, Nicola (författare)
Waters Corporation, Wilmslow, UK
Nothias, Louis-Félix (författare)
University of Geneva, Geneva, Switzerland; Université Côte d'Azur, CNRS, ICN, Nice, France
Hyötyläinen, Tuulia, 1971- (författare)
Örebro universitet,Institutionen för naturvetenskap och teknik
Oresic, Matej, 1967- (författare)
Örebro universitet,Institutionen för medicinska vetenskaper,University of Turku and Åbo Akademi University, Turku, Finland
Karst, Uwe (författare)
University of Münster, Münster, Germany
Dorrestein, Pieter C. (författare)
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
Petras, Daniel (författare)
University of Tuebingen, Tuebingen, Germany; University of California Riverside, Riverside, CA, USA
Du, Xiuxia (författare)
University of North Carolina at Charlotte, Charlotte, NC, USA
van der Hooft, Justin J. J. (författare)
Wageningen University & Research, Wageningen, the Netherlands; University of Johannesburg, Johannesburg, South Africa
Schmid, Robin (författare)
University of Münster, Münster, Germany; Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
Pluskal, Tomáš (författare)
Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
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 (creator_code:org_t)
2024
2024
Engelska.
Ingår i: Nature Protocols. - : Nature Publishing Group. - 1754-2189 .- 1750-2799.
Relaterad länk:
https://urn.kb.se/re...
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https://doi.org/10.1...
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  • Forskningsöversikt (refereegranskat)
Abstract Ämnesord
Stäng  
  • Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography-MS, gas chromatography-MS and MS-imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography-(IMS-)MS, gas chromatography-MS and (IMS-)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Bioinformatics (hsv//eng)

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