R-chie overlapping covariance 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
FIGURE 3:
An example of an ‘overlapping covariance arc diagram’, of the TRANSAT predicted structure, overlapping the RFAM consensus structure of family RF00458 . The colouring of arcs indicates their P-value from best (blue) to worst (red) and gray for conflicting base pairs. Between the arcs are two covariance blocks representing the same seven sequences in a gapped multiple sequence alignment from RFAM. Unpaired nucleotides are in black and gaps are in gray. For columns at the ends of a single non-conflicting arc, bases are assigned green if they are valid base pairs (G:C, A:U, G:U and the reversed pairings), or else they are red. For the green valid base pairs, if the base pair varies from the most commonly observed base pair in the column, then it is coloured blue to signify co-variation, or compensatory mutations to retain the base-pairing potential of the positions (dark blue for two sided, and light blue for one sided). The colouring of base pairs for arcs gives a qualitative representation of how well the base pair is conserved, and can be used to infer the validity of predicted base pairs, or the quality of an alignment given a known structure. For example, while most of the novel base pairs predicted to exist are simply extensions or slight shifts of known helices, the three largest red helices in the bottom show very high sequence conservation.
ABSTRACT:
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.
R-chie overlapping covariance 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
FIGURE 3:
An example of an ‘overlapping covariance arc diagram’, of the TRANSAT predicted structure, overlapping the RFAM consensus structure of family RF00458 . The colouring of arcs indicates their P-value from best (blue) to worst (red) and gray for conflicting base pairs. Between the arcs are two covariance blocks representing the same seven sequences in a gapped multiple sequence alignment from RFAM. Unpaired nucleotides are in black and gaps are in gray. For columns at the ends of a single non-conflicting arc, bases are assigned green if they are valid base pairs (G:C, A:U, G:U and the reversed pairings), or else they are red. For the green valid base pairs, if the base pair varies from the most commonly observed base pair in the column, then it is coloured blue to signify co-variation, or compensatory mutations to retain the base-pairing potential of the positions (dark blue for two sided, and light blue for one sided). The colouring of base pairs for arcs gives a qualitative representation of how well the base pair is conserved, and can be used to infer the validity of predicted base pairs, or the quality of an alignment given a known structure. For example, while most of the novel base pairs predicted to exist are simply extensions or slight shifts of known helices, the three largest red helices in the bottom show very high sequence conservation.
ABSTRACT:
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.