R-chie double structure arc diagram by Daniel Lai, Jeff Proctor, Jing Yun and Irmtraud Meyer
Creative Commons licensed image via R-chie: a web server and R package for visualizing RNA secondary structures by: Daniel Lai, Jeff R. Proctor, Jing Yun, Irmtraud M. Meyer
Nucleic Acids Research, Vol. 40, No. 12. (01 July 2012), pp. e95-e95, dx.doi.org/10.1093/nar/gks241
An example of a ‘double structure arc diagram’, showing the Cripavirus Internal Ribosomal Entry Site [family RF00458 from the RFAM database]. The RNA secondary structure shown above the horizontal sequence line has been predicted by TRANSAT. Every arc corresponds to one base pair whose colour indicates its P-value, where dark blue is ≤1e-06, light blue is ≤1e-05, orange is ≤1e-04 and red is ≤1e-03 (P-value threshold). The RNA structure shown below the horizontal sequence line shows the consensus RNA structure from RFAM.
Visually examining RNA structures can greatly aid in understanding their potential functional roles and in evaluating the performance of structure prediction algorithms. As many functional roles of RNA structures can already be studied given the secondary structure of the RNA, various methods have been devised for visualizing RNA secondary structures. Most of these methods depict a given RNA secondary structure as a planar graph consisting of base-paired stems interconnected by roundish loops. In this article, we present an alternative method of depicting RNA secondary structure as arc diagrams. This is well suited for structures that are difficult or impossible to represent as planar stem-loop diagrams. Arc diagrams can intuitively display pseudo-knotted structures, as well as transient and alternative structural features. In addition, they facilitate the comparison of known and predicted RNA secondary structures. An added benefit is that structure information can be displayed in conjunction with a corresponding multiple sequence alignments, thereby highlighting structure and primary sequence conservation and variation. We have implemented the visualization algorithm as a web server R-CHIE as well as a corresponding R package called R4RNA, which allows users to run the software locally and across a range of common operating systems.