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A short note on dynamic programming in a band
1MaIAGE, INRA, Université Paris-Saclay, Jouy-en-Josas, 78350, France. jean-francois.gibrat@inra.fr.
BMC Bioinformatics
|June 16, 2018
Summary
This study introduces a banded dynamic programming algorithm for efficiently aligning long sequencing reads, which often contain errors. This method optimizes sequence alignment for improved consensus generation from high-error data.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Third-generation sequencing technologies produce long reads with high error rates, particularly insertions and deletions.
- Exact sequence alignment with insertions and deletions typically relies on dynamic programming algorithms.
Purpose of the Study:
- To develop an efficient algorithm for aligning long sequencing reads.
- To address the challenge of high error rates in long reads.
Main Methods:
- Implementing dynamic programming within a defined band for computational efficiency.
- Determining optimal band width based on long read error rates.
- Developing a procedure to assess score optimality for semi-global alignments.
Main Results:
- An algorithm achieving [Formula: see text] time and space complexity for sequence alignment.
- A method for selecting band width tailored to specific error rates.
- A procedure to validate the optimality of semi-global alignment scores.
Conclusions:
- Banded dynamic programming is suitable for aligning long reads.
- This approach can be a core component for generating consensus sequences from long reads.
- A standalone program implementing the algorithm is publicly available.
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