Automated analysis of small RNA datasets with RAPID

Sivarajan Karunanithi; Martin Simon; Marcel H Schulz

doi:10.7717/peerj.6710

Automated analysis of small RNA datasets with RAPID

PeerJ. 2019 Apr 10:7:e6710. doi: 10.7717/peerj.6710. eCollection 2019.

Authors

Sivarajan Karunanithi^{1

2

3}, Martin Simon⁴, Marcel H Schulz^{1

3

5}

Affiliations

¹ Cluster of Excellence for Multimodal Computing and Interaction, and Department for Computational Biology & Applied Algorithms, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, Germany.
² Graduate School of Computer Science, Saarland Informatics Campus, Universität des Saarlandes, Saarbrücken, Germany.
³ Institute for Cardiovascular Regeneration, Goethe University Hospital, Frankfurt am Main, Germany.
⁴ Molecular Cell Biology and Microbiology, Wuppertal University, Wuppertal, Germany.
⁵ German Centre for Cardiovascular Research (DZHK), Partner site RheinMain, Frankfurt am Main, Germany.

Abstract

Understanding the role of short-interfering RNA (siRNA) in diverse biological processes is of current interest and often approached through small RNA sequencing. However, analysis of these datasets is difficult due to the complexity of biological RNA processing pathways, which differ between species. Several properties like strand specificity, length distribution, and distribution of soft-clipped bases are few parameters known to guide researchers in understanding the role of siRNAs. We present RAPID, a generic eukaryotic siRNA analysis pipeline, which captures information inherent in the datasets and automatically produces numerous visualizations as user-friendly HTML reports, covering multiple categories required for siRNA analysis. RAPID also facilitates an automated comparison of multiple datasets, with one of the normalization techniques dedicated for siRNA knockdown analysis, and integrates differential expression analysis using DESeq2.

Availability and implementation: RAPID is available under MIT license at https://github.com/SchulzLab/RAPID. We recommend using it as a conda environment available from https://anaconda.org/bioconda/rapid.

Keywords: Automated sRNA analysis; Comparative analysis; Computational sRNA analysis; Eukaryotic sRNA; Small RNA analysis; sRNA; sRNA tool; siRNA analysis; siRNA quantification.

Grants and funding

This work was supported by grants from the German Research Council (DFG) to Martin Simon (SI1379/3-1) and to Marcel H. Schulz (SCHU3140/1-1). The Max Planck Society funded the Article Processing Charge (APC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.