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 ImplementationRAPID 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
Highlights
Widespread availability of small RNA sequencing technologies drives the biological community in unraveling the pivotal role of sRNA molecules
We show the application of RAPID on two different datasets, highlighting some features that can be investigated by doing a standard RAPID analysis
Our first example is an analysis on four sRNA-seq datasets (ENA: PRJEB25903) from wildtype serotypes (51A, 51B, 51D, and 51H) of P. tetraurelia
Summary
Widespread availability of small RNA (sRNA) sequencing technologies drives the biological community in unraveling the pivotal role of sRNA molecules. Micro RNA (miRNA), short interfering RNA (siRNA), piwi-interacting RNA (piRNA), small nucleolar RNA (snoRNA), and trans-acting RNA (taRNA) are some members of the sRNA family. In a wide range of organisms, these sRNA molecules play crucial roles in gene regulation (Bossi & FigueroaBossi, 2016). MiRNAs are the most widely studied sRNA molecules, a growing interest can be seen in other sRNA classes, like siRNAs. With improved mechanistic understanding of siRNA function, siRNAs are increasingly used as therapeutic agents in. How to cite this article Karunanithi S, Simon M, Schulz MH. Automated analysis of small RNA datasets with RAPID. Using siRNAs in therapy requires a solid understanding of siRNA biogenesis, and behavior
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
