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Bioinformatics Advance Access published online on October 12, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl514
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received June 28, 2006
Revised October 4, 2006
Accepted October 4, 2006

Article

Measuring covariation in RNA alignments: physical realism improves information measures

S. Lindgreen 1 *, P. P. Gardner 2, and A. Krogh 1

1 Bioinformatics Centre, University of Copenhagen, Universitetsparken 15, 2100 Copenhagen Ø, Denmark
2 Molecular Evolution Group, Institute of Molecular Biology, University of Copenhagen, Universitetsparken 15, 2100 Copenhagen Ø, Denmark

* To whom correspondence should be addressed.
S. Lindgreen, E-mail: stinus{at}binf.ku.dk


  Abstract

Motivation: The importance of non-coding RNAs is becoming increasingly evident, and often the function of these molecules depends on the structure. It is common to use alignments of related RNA sequences to deduce the consensus secondary structure by detecting patterns of co-evolution. A central part of such an analysis is to measure covariation between two positions in an alignment. Here, we rank various measures ranging from simple mutual information to more advanced covariation measures.

Results: Mutual information is still used for secondary structure prediction, but the results of this study indicate which measures are useful. Incorporating more structural information by considering e.g. indels and stacking improves accuracy, suggesting that physically realistic measures yield improved predictions. This can be used to improve both current and future programs for secondary structure prediction. The best measure tested is the RNAalifold covariation measure modified to include stacking.

Availability: Scripts, data and supplementary material can be found at http://www.binf.ku.dk/Stinus_covariation.

Associate Editor: Golan Yona
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