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RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences.


ABSTRACT:

Motivation

RNA secondary structure plays an important role in the function of many RNAs, and structural features are often key to their interaction with other cellular components. Thus, there has been considerable interest in the prediction of secondary structures for RNA families. In this article, we present a new global structural alignment algorithm, RNAG, to predict consensus secondary structures for unaligned sequences. It uses a blocked Gibbs sampling algorithm, which has a theoretical advantage in convergence time. This algorithm iteratively samples from the conditional probability distributions P(Structure | Alignment) and P(Alignment | Structure). Not surprisingly, there is considerable uncertainly in the high-dimensional space of this difficult problem, which has so far received limited attention in this field. We show how the samples drawn from this algorithm can be used to more fully characterize the posterior space and to assess the uncertainty of predictions.

Results

Our analysis of three publically available datasets showed a substantial improvement in RNA structure prediction by RNAG over extant prediction methods. Additionally, our analysis of 17 RNA families showed that the RNAG sampled structures were generally compact around their ensemble centroids, and at least 11 families had at least two well-separated clusters of predicted structures. In general, the distance between a reference structure and our predicted structure was large relative to the variation among structures within an ensemble.

Availability

The Perl implementation of the RNAG algorithm and the data necessary to reproduce the results described in Sections 3.1 and 3.2 are available at http://ccmbweb.ccv.brown.edu/rnag.html

Contact

charles_lawrence@brown.edu

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Wei D 

PROVIDER: S-EPMC3167047 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences.

Wei Donglai D   Alpert Lauren V LV   Lawrence Charles E CE  

Bioinformatics (Oxford, England) 20110724 18


<h4>Motivation</h4>RNA secondary structure plays an important role in the function of many RNAs, and structural features are often key to their interaction with other cellular components. Thus, there has been considerable interest in the prediction of secondary structures for RNA families. In this article, we present a new global structural alignment algorithm, RNAG, to predict consensus secondary structures for unaligned sequences. It uses a blocked Gibbs sampling algorithm, which has a theoret  ...[more]

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