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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 1:
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.
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.
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
COVER
An arc diagram created using the R-chie web-server showing RNA base pair predictions by two programs for an alignment of Cripavirus IRES homologs (Rfam family RF00458). Each horizontal line represents a sequence of the alignment, and each arc represents a predicted base pair between two positions of the sequence. The same alignment comprising seven sequences is drawn for each prediction (top and bottom), highlighting the degree of evolutionary conservation for each predicted base pair: conserved base pairs (green), co-varying base pairs (dark and light blue), and invalid base pairs (red). Unpaired bases are in black and gaps in grey. The top arcs represent base pairs predicted by the program Transat, coloured by increasing statistical significance from dark to light blue, with mutually exclusive predictions in grey. The bottom arcs correspond to base pairs corresponding the RNA secondary structure predicted by Mfold for the first sequence of the alignment. Base pairs are coloured by increasing amount of covariation, from dark to light orange. The R-chie web server and the underlying R package R4RNA are freely available at www.e-rna.org/r-chie/.
ASBSTRACT
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.
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.
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 2
An example of a ‘overlapping structure arc diagram’, overlapping the TRANSAT predicted structure and the RFAM consensus structure of family RF00458. The structure shown above the horizontal sequence is the known structure in black, coloured by P-value if correctly predicted by TRANSAT (best in blue and worst in red). The arcs below the line represent novel base pairs predicted by TRANSAT not found in the known RFAM structure. Such a diagram can give} a qualitative description of a predicted structure's performance, where high sensitivity would result in a high proportion of top helices being coloured, and high specificity would result in a majority of helices above the line. On the other hand, the novel base pairs observed on the bottom half, may indicate alternative structural elements not yet experimentally verified, but worth investigating, especially in light of strong evolutionary evidence.
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.
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