Reproducible mass spectrometry data processing and compound annotation in MZmine 3
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388963%3A_____%2F24%3A00586544" target="_blank" >RIV/61388963:_____/24:00586544 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11110/24:10482661
Result on the web
<a href="https://doi.org/10.1038/s41596-024-00996-y" target="_blank" >https://doi.org/10.1038/s41596-024-00996-y</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41596-024-00996-y" target="_blank" >10.1038/s41596-024-00996-y</a>
Alternative languages
Result language
angličtina
Original language name
Reproducible mass spectrometry data processing and compound annotation in MZmine 3
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10608 - Biochemistry and molecular biology
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Nature Protocols
ISSN
1754-2189
e-ISSN
1750-2799
Volume of the periodical
19
Issue of the periodical within the volume
9
Country of publishing house
US - UNITED STATES
Number of pages
45
Pages from-to
2597-2641
UT code for WoS article
001228380000001
EID of the result in the Scopus database
2-s2.0-85193731416