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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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R-PASS: A Fast Structure-based RNA Sequence Alignment Algorithm.

Yanan Jiang1, Weijia Xu2, Lee Parnell Thompson3

  • 1Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, USA.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine
|April 29, 2014
PubMed
Summary
This summary is machine-generated.

We developed R-PASS (RNA Pairwise Alignment of Structure and Sequence), a fast and accurate method for aligning RNA sequences using structural information, outperforming existing tools in speed and precision for low sequence identity cases.

Keywords:
RNA pairwise structural alignmentbipartite graph matchingconstraint sequence alignmentstructure motif

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Molecular biology

Background:

  • RNA sequence alignment is crucial for understanding RNA function and evolution.
  • Existing methods struggle with accuracy and speed, especially for sequences with low identity.
  • Structure-based alignment offers a promising avenue for improved RNA analysis.

Purpose of the Study:

  • To introduce R-PASS, a novel method for fast and accurate pairwise RNA sequence alignment.
  • To leverage RNA secondary structure information for enhanced alignment accuracy.
  • To demonstrate the superior performance of R-PASS compared to existing alignment tools.

Main Methods:

  • RNA secondary structures are represented as sets of structure motifs.
  • A bipartite graph-matching algorithm identifies structure matches between two RNAs.
  • Structure matches serve as constraints in a dynamic programming sequence alignment.
  • The R-PASS method achieves a time complexity of O(nm).

Main Results:

  • R-PASS demonstrates high accuracy, particularly for RNA sequences with low sequence identity.
  • The method is significantly faster, orders of magnitude, than alternative structure-based and sequence-based alignment tools.
  • Comparative benchmarks against LARA, ExpaLoc, and MAFFT show favorable results for R-PASS.

Conclusions:

  • R-PASS provides a computationally efficient and accurate solution for pairwise RNA sequence alignment.
  • The integration of structural information effectively improves alignment quality.
  • R-PASS represents a significant advancement in RNA sequence analysis tools.