About: The metaRbolomics Toolbox in Bioconductor and beyond

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	The metaRbolomics Toolbox in Bioconductor and beyond
Creator	Helmus, Rick Hoffmann, Nils Mathé, Ewy Naake, Thomas Neumann, Steffen Nicolotti, Luca Peters, Kristian Rainer, Johannes Schulze, Tobias Stanstrup, Jan Treutler, Hendrik Willighagen, Egon Witting, Michael Broeckling, Corey Salek, Reza Schymanski, Emma Stravs, Michael Thévenot, Etienne Weber, Ralf
Source	PMC
abstract	Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub.
has issue date	2019-09-23(xsd:dateTime)
bibo:doi	10.3390/metabo9100200
bibo:pmid	31548506
has license	cc-by
sha1sum (hex)	8c44e37bccf0c2a493e1b1754081384fc802d3d9
schema:url	https://doi.org/10.3390/metabo9100200
resource representing a document's title	The metaRbolomics Toolbox in Bioconductor and beyond
has PubMed Central identifier	PMC6835268
has PubMed identifier	31548506
schema:publication	Metabolites
resource representing a document's body	covid:8c44e37bccf0c2a493e1b1754081384fc802d3d9#body_text
is schema:about of	named entity 'SCIENCE' named entity 'PROVIDING' named entity 'PROCESS' named entity 'STUDIES' named entity 'WORKFLOW' named entity 'WIDE' named entity 'MASS SPECTROMETRY' named entity 'INTEGRATION' named entity 'COMPLEX COMPOSITION' named entity 'PATHWAY ANALYSIS' named entity 'ALLOWS' named entity 'IDENTIFICATION' named entity 'REUSABLE' named entity 'SCRIPTS' named entity 'RESEARCH' named entity 'PROVIDES' named entity 'PROCESSING' named entity 'INTEREST' named entity 'MAJOR' named entity 'REVIEWED' named entity 'MORE THAN' named entity 'GENERATE' named entity 'AVAILABLE' named entity 'RANGE' named entity 'TOOLS' named entity 'APPROACHES' named entity 'USER INTERFACES' named entity 'EXTENSIVE' named entity 'NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY' named entity 'COMBINING' named entity 'ANALYTICAL TECHNIQUES' named entity 'CONNECTING' named entity 'COMMUNITY' named entity 'COMPUTATIONAL' named entity 'ANNOTATION' named entity 'TOTAL' named entity 'LARGE' named entity 'AMOUNTS' named entity 'SOURCE' named entity 'COMPLEX' named entity 'AIMS' named entity 'BIOSTATISTICS' named entity 'BIOCONDUCTOR' named entity 'METABOLITES' named entity 'BEYOND' named entity 'ENVIRONMENTS' named entity 'BIOCONDUCTOR' named entity 'STATISTICS' named entity 'PROGRAMMING' named entity 'ADVANCED' named entity 'STEPS' named entity 'A MAJOR' named entity 'SPECIFIC' named entity 'INCLUDING' named entity 'EXPERIMENTAL DATA' named entity 'DATA PROCESSING' named entity 'HIGH' named entity 'REVIEW' named entity 'POSSIBILITY OF' named entity 'OPEN SOURCE SOFTWARE' named entity 'POSSIBLE' named entity 'DIFFERENT' named entity 'OVERVIEW'

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