RNAcomp2D: a visual tool to compare multiple predictions of RNA secondary structure

Abstract

Ribonucleic acids (RNAs) are involved in many important biological processes. In particular, non-coding RNAs are crucial regulators of cellular processes, playing a significant role in gene expression. RNA secondary structure is key to infer their specific function and for understanding how they interact with other molecules. Many computational models have been developed in the last decade to predict the secondary structure, achieving increasingly higher success rates. However, each new method has its own input-output interface, programming language, computational requirements and, sometimes, a dedicated server to run the model or just a source code in a repository. Thus, nowadays it is very hard to obtain predictions from multiple methods and compare them at once. A unified interface is urgently needed, which allows accessing several methods at the same time, visualizing and comparing predictions among them, and also with a reference structure when available. We introduce here RNAcomp2D, a web-based tool that allows users to enter an RNA sequence, or select one from RNAcentral, and obtains predictions of RNA secondary structures using several state-of-the-art methods. Both classical thermodynamic methods and the latest deep learning models are packaged in containers and accessible in an unified website. All the predictions, and the reference structure if available, are shown at the same time in a single graphical interface. Moreover, as new models continue to be developed, this tool is designed to be scalable, allowing the addition of more prediction methods in the future. Web server is available at https://sinc.unl.edu.ar/web-demo/rnacomp2d/. Data and source code are available at https://github.com/sinc-lab/RNAcomp2D