Konrad U Förstner1, Jörg Vogel2, Cynthia M Sharma2. 1. Institute for Molecular Infection Biology and Research Centre for Infectious Diseases (ZINF), University of Würzburg, D-97080 Würzburg, Germany Institute for Molecular Infection Biology and Research Centre for Infectious Diseases (ZINF), University of Würzburg, D-97080 Würzburg, Germany. 2. Institute for Molecular Infection Biology and Research Centre for Infectious Diseases (ZINF), University of Würzburg, D-97080 Würzburg, Germany.
Abstract
UNLABELLED: RNA-Seq has become a potent and widely used method to qualitatively and quantitatively study transcriptomes. To draw biological conclusions based on RNA-Seq data, several steps, some of which are computationally intensive, have to be taken. Our READemption pipeline takes care of these individual tasks and integrates them into an easy-to-use tool with a command line interface. To leverage the full power of modern computers, most subcommands of READemption offer parallel data processing. While READemption was mainly developed for the analysis of bacterial primary transcriptomes, we have successfully applied it to analyze RNA-Seq reads from other sample types, including whole transcriptomes and RNA immunoprecipitated with proteins, not only from bacteria but also from eukaryotes and archaea. AVAILABILITY AND IMPLEMENTATION: READemption is implemented in Python and is published under the ISC open source license. The tool and documentation is hosted at http://pythonhosted.org/READemption (DOI:10.6084/m9.figshare.977849).
UNLABELLED: RNA-Seq has become a potent and widely used method to qualitatively and quantitatively study transcriptomes. To draw biological conclusions based on RNA-Seq data, several steps, some of which are computationally intensive, have to be taken. Our READemption pipeline takes care of these individual tasks and integrates them into an easy-to-use tool with a command line interface. To leverage the full power of modern computers, most subcommands of READemption offer parallel data processing. While READemption was mainly developed for the analysis of bacterial primary transcriptomes, we have successfully applied it to analyze RNA-Seq reads from other sample types, including whole transcriptomes and RNA immunoprecipitated with proteins, not only from bacteria but also from eukaryotes and archaea. AVAILABILITY AND IMPLEMENTATION: READemption is implemented in Python and is published under the ISC open source license. The tool and documentation is hosted at http://pythonhosted.org/READemption (DOI:10.6084/m9.figshare.977849).
Authors: Maureen K Thomason; Thorsten Bischler; Sara K Eisenbart; Konrad U Förstner; Aixia Zhang; Alexander Herbig; Kay Nieselt; Cynthia M Sharma; Gisela Storz Journal: J Bacteriol Date: 2014-09-29 Impact factor: 3.490
Authors: B Remes; T Rische-Grahl; K M H Müller; K U Förstner; Sung-Huan Yu; L Weber; A Jäger; V Peuser; G Klug Journal: J Bacteriol Date: 2017-06-27 Impact factor: 3.490
Authors: Philip Möller; Philip Busch; Beate Sauerbrei; Alexander Kraus; Konrad U Förstner; Tuan-Nan Wen; Aaron Overlöper; Erh-Min Lai; Franz Narberhaus Journal: J Bacteriol Date: 2019-05-08 Impact factor: 3.490
Authors: Judith S Bauer; Sven Fillinger; Konrad Förstner; Alexander Herbig; Adam C Jones; Katrin Flinspach; Cynthia Sharma; Harald Gross; Kay Nieselt; Alexander K Apel Journal: RNA Biol Date: 2017-07-31 Impact factor: 4.652
Authors: Gaurav Dugar; Ryan T Leenay; Sara K Eisenbart; Thorsten Bischler; Belinda U Aul; Chase L Beisel; Cynthia M Sharma Journal: Mol Cell Date: 2018-03-01 Impact factor: 17.970
Authors: Alexandre Smirnov; Konrad U Förstner; Erik Holmqvist; Andreas Otto; Regina Günster; Dörte Becher; Richard Reinhardt; Jörg Vogel Journal: Proc Natl Acad Sci U S A Date: 2016-09-26 Impact factor: 11.205