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Hastreiter, M. ; Jeske, T. ; Hoser, J.D.S. ; Kluge, M. ; Ahomaa, K. ; Friedl, M.-S. ; Kopetzky, S.J. ; Quell, J. ; Mewes, H.-W. ; Küffner, R.

KNIME4NGS: A comprehensive toolbox for next generation sequencing analysis.

Bioinformatics 33, 1565-1567 (2017)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Analysis of Next Generation Sequencing (NGS) data requires the processing of large datasets by chaining various tools with complex input and output formats. In order to automate data analysis, we propose to standardize NGS tasks into modular workflows. This simplifies reliable handling and processing of NGS data, and corresponding solutions become substantially more reproducible and easier to maintain. Here, we present a documented, linux-based, toolbox of 42 processing modules that are combined to construct workflows facilitating a variety of tasks such as DNAseq and RNAseq analysis. We also describe important technical extensions. The high throughput executor (HTE) helps to increase the reliability and to reduce manual interventions when processing complex datasets. We also provide a dedicated binary manager that assists users in obtaining the modules' executables and keeping them up to date. As basis for this actively developed toolbox we use the workflow management software KNIME.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Sprache
Veröffentlichungsjahr 2017
HGF-Berichtsjahr 2017
e-ISSN 1367-4811
Zeitschrift Bioinformatics
Quellenangaben Band: 33, Heft: 10, Seiten: 1565-1567 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Verlagsort Oxford
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)
POF Topic(s) 30505 - New Technologies for Biomedical Discoveries
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503700-001
DOI 10.1093/bioinformatics/btx003
WOS ID WOS:000402130700018
Scopus ID 85020285279
PubMed ID 28172527
Erfassungsdatum 2017-06-02
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