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

- Accessible workflow frameworks for RNA-Seq analysis are presented.
- Tools for RNA-Seq data processing and differential expression analysis are discussed.
- The identification of bacterial sRNAs and their targets is reviewed.
- Differential RNA-Seq of microbial communities (mdRNA-Seq) is explained.
- The state of the art of integrating RNA-Seq with other data is outlined.

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).

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