Automated analysis and comparison of multiple small RNA datasets with RAPID

The role of small RNA (sRNA) molecules in genome regulation is not yet fully understood. Micro RNAs (miRNA), small interfering RNAs (siRNA), piwi-interacting RNAs (piRNA), and trans-acting RNAs (taRNA) are some members of the sRNA family. Existing sRNA analysis tools predominantly focus on predicting novel miRNAs, piRNAs, and quantifying them. This leads to either ignoring other classes of sRNA or require custom made scripts. Understanding the role of these sRNAs in diverse biological processes requires paying attention to minor details, e.g. sRNAs originating from different strands in varying lengths, have different targets to involve in different downstream pathway.  No integrated computational solution exists to investigate novel sRNA data in an unbiased way. Hence, we developed a generic sRNA analysis tool capturing read counts along with strand specificity, length distribution, and base modification. Our tool also automatically produces numerous visualizations covering multiple categories required for sRNA analysis. Our tool allows various normalization techniques to compare different sRNA samples, tailored to different scenarios e.g. knockdown of RNA interference components in the model organism. All analyses can be restricted to certain read lengths. For ease of use, our tool integrates an automated differential expression analysis using DESeq2.  Here, we present some example outputs from our tool. With no doubt, our tool is designed to simplify the life of data analysts and introduces a different perspective of available data. Our tool, RAPID is available at: https://github.com/SchulzLab/RAPID .