Exploration and analysis of R-loop mapping data with RLBase

Abstract

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 R-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/.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 30, 2022
Source ID
10.1093/nar/gkac732

Entities

People

  • Alexander J R Bishop
  • Bess Frost
  • Daniel Montemayor
  • Frédéric Chedin
  • Henry E Miller
  • Janet Li
  • Kumar Sharma
  • Roshan Pawar
  • Simon A Levy
  • Stella Hartono

Organizations

  • Cancer Prevention and Research Institute of Texas
  • National Institutes of Health
  • United States Department of Defense
  • University of British Columbia
  • University of California, Davis
  • University of Texas Health Science Center at San Antonio

Tags

Readers

  • Computer Science.
  • Molecular Genetics
  • Neural Network Machine Learning.

Technology Areas

  • Biotechnology