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Flexible metagenome analysis using the MGX framework

Jaenicke, Sebastian ; Albaum, Stefan P. ; Blumenkamp, Patrick ; Linke, Burkhard ; Stoye, Jens ; Goesmann, Alexander


Originalveröffentlichung: (2018) Microbiome 6:76 doi: 10.1186/s40168-018-0460-1
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URN: urn:nbn:de:hebis:26-opus-153590
URL: http://geb.uni-giessen.de/geb/volltexte/2020/15359/


Sammlung: Open Access - Publikationsfonds
Universität Justus-Liebig-Universit√§t Gie√üen
Institut: Bioinformatics and Systems Biology
Fachgebiet: Biologie
DDC-Sachgruppe: Biowissenschaften, Biologie
Dokumentart: Aufsatz
Sprache: Englisch
Erstellungsjahr: 2018
Publikationsdatum: 03.08.2020
Kurzfassung auf Englisch: BACKGROUND: The characterization of microbial communities based on sequencing and analysis of their genetic information has become a popular approach also referred to as metagenomics; in particular, the recent advances in sequencing technologies have enabled researchers to study even the most complex communities. Metagenome analysis, the assignment of sequences to taxonomic and functional entities, however, remains a tedious task: large amounts of data need to be processed. There are a number of approaches addressing particular aspects, but scientific questions are often too specific to be answered by a general-purpose method.
RESULTS: We present MGX, a flexible and extensible client/server-framework for the management and analysis of metagenomic datasets; MGX features a comprehensive set of adaptable workflows required for taxonomic and functional metagenome analysis, combined with an intuitive and easy-to-use graphical user interface offering customizable result visualizations. At the same time, MGX allows to include own data sources and devise custom analysis pipelines, thus enabling researchers to perform basic as well as highly specific analyses within a single application.
CONCLUSIONS: With MGX, we provide a novel metagenome analysis platform giving researchers access to the most recent analysis tools. MGX covers taxonomic and functional metagenome analysis, statistical evaluation, and a wide range of visualizations easing data interpretation. Its default taxonomic classification pipeline provides equivalent or superior results in comparison to existing tools.
Lizenz: Lizenz-Logo  Creative Commons - Namensnennung 4.0