Customized workflow development and data modularization concepts for RNA-Sequencing and metatranscriptome experiments

Steffen C Lott; Markus Wolfien; Konstantin Riege; Andrea Bagnacani; Olaf Wolkenhauer; Steve Hoffmann; Wolfgang R Hess

doi:10.1016/j.jbiotec.2017.06.1203

Customized workflow development and data modularization concepts for RNA-Sequencing and metatranscriptome experiments

J Biotechnol. 2017 Nov 10:261:85-96. doi: 10.1016/j.jbiotec.2017.06.1203. Epub 2017 Jul 1.

Authors

Steffen C Lott¹, Markus Wolfien², Konstantin Riege³, Andrea Bagnacani², Olaf Wolkenhauer⁴, Steve Hoffmann³, Wolfgang R Hess⁵

Affiliations

¹ Genetics and Experimental Bioinformatics, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104 Freiburg, Germany.
² Department of Systems Biology & Bioinformatics, University of Rostock, Ulmenstr. 69, 18057 Rostock, Germany.
³ Transcriptome Bioinformatics Group, LIFE Research Complex, University Leipzig, Härtelstrasse 16-18, 04107 Leipzig, Germany.
⁴ Department of Systems Biology & Bioinformatics, University of Rostock, Ulmenstr. 69, 18057 Rostock, Germany; Stellenbosch Institute of Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, 7602 Stellenbosch, South Africa.
⁵ Genetics and Experimental Bioinformatics, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104 Freiburg, Germany. Electronic address: wolfgang.hess@biologie.uni-freiburg.de.

PMID: 28676233
DOI: 10.1016/j.jbiotec.2017.06.1203

Abstract

RNA-Sequencing (RNA-Seq) has become a widely used approach to study quantitative and qualitative aspects of transcriptome data. The variety of RNA-Seq protocols, experimental study designs and the characteristic properties of the organisms under investigation greatly affect downstream and comparative analyses. In this review, we aim to explain the impact of structured pre-selection, classification and integration of best-performing tools within modularized data analysis workflows and ready-to-use computing infrastructures towards experimental data analyses. We highlight examples for workflows and use cases that are presented for pro-, eukaryotic and mixed dual RNA-Seq (meta-transcriptomics) experiments. In addition, we are summarizing the expertise of the laboratories participating in the project consortium "Structured Analysis and Integration of RNA-Seq experiments" (de.STAIR) and its integration with the Galaxy-workbench of the RNA Bioinformatics Center (RBC).

Keywords: Metatranscriptomics; Regulatory RNA; Transcriptomics; Workflow development.

Publication types

Review

MeSH terms

Computational Biology*
Gene Expression Profiling
High-Throughput Nucleotide Sequencing
RNA* / analysis
RNA* / genetics
RNA* / metabolism
Sequence Analysis, RNA*
Transcriptome*

Substances

RNA