LinAliFold and CentroidLinAliFold: Fast RNA consensus secondary structure prediction for aligned sequences using beam search methods

@article{Fukunaga2022LinAliFoldAC,
  title={LinAliFold and CentroidLinAliFold: Fast RNA consensus secondary structure prediction for aligned sequences using beam search methods},
  author={Tsukasa Fukunaga and Michiaki Hamada},
  journal={bioRxiv},
  year={2022}
}
RNA consensus secondary structure prediction from aligned sequences is a powerful approach for improving the secondary structure prediction accuracy. However, because the computational complexities of conventional prediction tools scale with the cube of the alignment lengths, their application to long RNA sequences, such as viral RNAs or long non-coding RNAs, requires significant computational time. In this study, we developed LinAliFold and CentroidLinAli-Fold, fast RNA consensus secondary… 

References

SHOWING 1-10 OF 48 REFERENCES
ConsAlifold: considering RNA structural alignments improves prediction accuracy of RNA consensus secondary structures
TLDR
This work developed and implemented ConsAlifold, a dynamic programming-based method that predicts the consensus secondary structure of an RNA sequence alignment and achieves moderate running time and the best prediction accuracy of RNA consensus secondary structures among available prediction methods.
Improving the accuracy of predicting secondary structure for aligned RNA sequences
TLDR
A theoretical classification of state-of-the-art algorithms of predicting secondary structure for aligned RNA sequences based on the viewpoint of maximum expected accuracy (MEA), which has been successfully applied in various problems in bioinformatics is presented.
CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction
TLDR
According to the authors' tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold, whereas the best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available.
Robust prediction of consensus secondary structures using averaged base pairing probability matrices
TLDR
This paper investigates the dependence of the accuracy of secondary structure prediction on the quality of alignments and shows that the McCaskill-MEA method performs better than other methods, particularly when the alignment quality is low and when the alignments consists of many sequences.
SCARNA: fast and accurate structural alignment of RNA sequences by matching fixed-length stem fragments
TLDR
A new method of comparing RNA sequences based on the structural alignments of the fixed-length fragments of the stem candidates, SCARNA (Stem Candidate Aligner for RNAs), is proposed and is fast enough to apply to the long sequences in the large-scale analyses.
TurboFold II: RNA structural alignment and secondary structure prediction informed by multiple homologs
TLDR
TurboFold II augments the structure prediction capabilities of TurboFold by additionally providing multiple sequence alignments, and has comparable alignment accuracy with MAFFT and higher accuracy than other tools.
Prediction of RNA secondary structure including pseudoknots for long sequences
TLDR
An improvement of IPknot is proposed that enables calculation in linear time by employing the LinearPartition model and automatically selects the optimal threshold parameters based on the pseudo-expected accuracy.
RNAalifold: improved consensus structure prediction for RNA alignments
TLDR
The accuracy of RNAalifold predictions can be improved substantially by introducing a different, more rational handling of alignment gaps, and by replacing the rather simplistic model of covariance scoring with more sophisticated RIBOSUM-like scoring matrices.
CentroidAlign: fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score
TLDR
A novel estimator for multiple alignments of structured RNAs is designed, which maximizes the expected sum-of-pairs score of a predicted alignment under a probability distribution of alignments given by marginalizing the Sankoff model and integrates the probabilistic consistency transformation on alignments into the proposed estimator.
Prediction of RNA secondary structure using generalized centroid estimators
TLDR
Novel estimators are proposed which improve the accuracy of secondary structure prediction of RNAs and represent extensions of the centroid estimators proposed in Ding et al. and Carvalho and Lawrence, and are applicable to a wide variety of problems in bioinformatics.
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