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

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. Here, University of Freiburg researchers 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. They highlight examples for workflows and use cases that are presented for pro-, eukaryotic and mixed dual RNA-Seq (meta-transcriptomics) experiments. In addition, they summarize 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).

Overview of possible data input formats (top), modularized workflow elements separated by certain tasks (middle; dark blue: in silico predictions; pink: linkage of epigenetic data; light blue: integration of further databases) and examples of subsequently generated output (bottom).