Exploration and analysis of R-loop mapping data with RLBase

R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. In 2012, Ginno et al. introduced the first R-loop mapping method. Since that time, dozens of R-loop mapping studies have been conducted, yielding hundreds of publicly available datasets. Current IR-loop databases provide only limited access to these data. Moreover, no web tools for analyzing user-supplied R-loop datasets have yet been described. In our recent work, we reprocessed 810 R-loop mapping samples, building the largest R-loop data resource to date. We also defined R-loop consensus regions and developed a framework for R-loop data analysis. Now, we introduce RLBase, a user-friendly database that provides the capability to (i) explore hundreds of public R-loop mapping datasets, (ii) explore R-loop consensus regions, (iii) analyze user-supplied data and (iv) download standardized and reprocessed datasets. RLBase is directly accessible via the following URL: https://gccri.bishop-lab. uthscsa.edu/shiny/rlbase/.

Automated summary

R-loops are structures formed by the hybridization of RNA and DNA, and extensive research has been conducted in recent years, resulting in a large number of datasets. However, current databases provide limited access to these data, and there are no web tools available for analyzing user-supplied R-loop datasets. In this study, we reprocessed 810 R-loop samples to create the largest R-loop data resource to date. We also developed a framework and user-friendly database, RLBase, which allows users to explore public R-loop datasets, analyze their own data, and download standardized datasets.