Technical advances in Next Generation Sequencing (NGS) provide a means to acquire deeper insights into cellular functions. The lack of standardized and automated methodologies poses a challenge for the analysis and interpretation of RNA sequencing data. Researchers at the University of Rostock critically compare and evaluate state-of-the-art bioinformatics approaches and present a workflow that integrates the best performing data analysis, data evaluation and annotation methods in a Transparent, Reproducible and Automated PipeLINE (TRAPLINE) for RNA sequencing data processing (suitable for Illumina, SOLiD and Solexa).
Comparative transcriptomics analyses with TRAPLINE result in a set of differentially expressed genes, their corresponding protein-protein interactions, splice variants, promoter activity, predicted miRNA-target interactions and files for single nucleotide polymorphism (SNP) calling. The obtained results are combined into a single file for downstream analysis such as network construction. We demonstrate the value of the proposed pipeline by characterizing the transcriptome of our recently described stem cell derived antibiotic selected cardiac bodies (‘aCaBs’).
Scheme to illustrate TRAPLINE’s RNA sequencing analyses modules
The target files are provided as Galaxy histories – miRNA Targets (usegalaxy.org/u/mwolfien/h/trapline-mirna-targets-input) and Protein-Protein Interactions (usegalaxy.org/u/mwolfien/h/trapline-protein-protein-interaction-input)
TRAPLINE supports NGS-based research by providing a workflow that requires no bioinformatics skills, decreases the processing time of the analysis and works in the cloud.
Availability – The pipeline is implemented in the biomedical research platform Galaxy and is freely accessible via www.sbi.uni-rostock.de/RNAseqTRAPLINE or the specific Galaxy manual page (https://usegalaxy.org/u/mwolfien/p/trapline—manual).