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Conserved Binding Sites01:49

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QuickEd: high-performance exact sequence alignment based on bound-and-align.

Max Doblas1,2, Oscar Lostes-Cazorla1,3, Quim Aguado-Puig1,3,4

  • 1Computer Sciences Department, Barcelona Supercomputing Center, Barcelona 08034, Spain.

Bioinformatics (Oxford, England)
|March 13, 2025
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Summary
This summary is machine-generated.

QuickEd offers optimal sequence alignment for long reads, overcoming scalability issues with a novel bound-and-align strategy. This method significantly speeds up analysis while maintaining accuracy and low memory usage.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Pairwise sequence alignment is crucial for analyzing sequencing data.
  • Long-read sequencing technologies are increasingly popular but pose scalability challenges for classical algorithms.
  • Existing heuristic methods often sacrifice accuracy for speed.

Purpose of the Study:

  • To introduce QuickEd, a novel sequence alignment algorithm designed for long and noisy sequencing data.
  • To address the scalability limitations of traditional alignment algorithms in the era of long-read sequencing.
  • To provide an accurate and efficient alignment tool that maintains optimal alignment.

Main Methods:

  • Developed QuickEd, utilizing a bound-and-align strategy.
  • Employs heuristic strategies to efficiently bound the maximum alignment score.
  • Reduces computational complexity from O(n^2) to O(ns^) for optimal alignment.

Main Results:

  • QuickEd achieves significant speedups compared to state-of-the-art tools like Edlib (4.2-5.9×) and BiWFA (3.8-4.4×).
  • Maintains optimal alignment accuracy for long and noisy datasets.
  • Demonstrates a stable memory footprint below 35 MB for sequences up to 1 Mbp.

Conclusions:

  • QuickEd provides a scalable and accurate solution for long-read sequence alignment.
  • The bound-and-align strategy effectively balances speed and accuracy.
  • QuickEd is a valuable tool for modern genomic data analysis.