The RNA workbench
The RNA workbench: best practices for RNA and high-throughput sequencing bioinformatics in Galaxy
BA. Grüning, J. Fallmann, D. Yusuf, S. Will, A. Erxleben, F. Eggenhofer, T. Houwaart, B. Batut, P. Videm, A. Bagnacani, M. Wolfien, SC. Lott, Y. Hoogstrate, WR. Hess, O. Wolkenhauer, S. Hoffmann, A. Akalin, U. Ohler, PF. Stadler, R. Backofen (2017): The RNA workbench: best practices for RNA and high-throughput sequencing bioinformatics in Galaxy Nucleic Acidc Research
The workflow for analyzing RNA-seq data. The workflow tolerates single-end and paired-end reads derived from different conditions. It employs TopHat2 for mapping and HTSeq-count to create the read counts. The final outputs contain read count per annotated gene for each condition and for each sequencing type.
RNA-based regulation has become a major research topic in molecular biology. The analysis of epigenetic and expression data is therefore incomplete if RNA-based regulation is not taken into account. Thus, it is increasingly important but not yet standard to combine RNA-centric data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq. Here, we present the RNA workbench, a comprehensive set of analysis tools and consolidated workflows that enable the researcher to combine these two worlds. Based on the Galaxy framework the workbench guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses that are independent of command-line knowledge. Currently, it includes more than 50 bioinformatics tools that are dedicated to different research areas of RNA biology including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. The workbench is developed and maintained by experts in RNA bioinformatics and the Galaxy framework. Together with the growing community evolving around this workbench, we are committed to keep the workbench up-to-date for future standards and needs, providing researchers with a reliable and robust framework for RNA data analysis.
The RNA workbench is available at github: https://github.com/bgruening/galaxy-rna-workbench