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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.
Abstract:
We present a fast pairwise RNA sequence alignment method using structural information, named R-PASS (RNA Pairwise Alignment of Structure and Sequence), which shows good accuracy on sequences with low sequence identity and significantly faster than alternative methods. The method begins by representing RNA secondary structure as a set of structure motifs. The motifs from two RNAs are then used as input into a bipartite graph-matching algorithm, which determines the structure matches. The matches are then used as constraints in a constrained dynamic programming sequence alignment procedure. The R-PASS method has an O(nm) complexity. We compare our method with two other structure-based alignment methods, LARA and ExpaLoc, and with a sequence-based alignment method, MAFFT, across three benchmarks and obtain favorable results in accuracy and orders of magnitude faster in speed.
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