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Finding maximal exact matches in graphs.

Nicola Rizzo1, Manuel Cáceres2, Veli Mäkinen2

  • 1Department of Computer Science, University of Helsinki, Pietari Kalmin katu 5, P.O. Box 68, Helsinki, 00014, Finland. nicola.rizzo@helsinki.fi.

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Summary
This summary is machine-generated.

This study presents an efficient algorithm for finding maximal exact matches (MEMs) in labeled graphs, crucial for bioinformatics. The new method significantly speeds up alignment processes on Elastic Founder Graphs, with fewer graph MEMs than string MEMs.

Keywords:
Bidirectional BWTFounder graphsSequence to graph alignmentSuffix treer-index

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Area of Science:

  • Computational Biology
  • Bioinformatics Algorithms
  • Graph Theory

Background:

  • Maximal Exact Matches (MEMs) are vital seeds in sequence alignment.
  • Finding MEMs in labeled graphs is computationally challenging.
  • Existing methods face limitations on arbitrary graphs due to SETH complexity.

Purpose of the Study:

  • Develop an efficient algorithm for finding k-MEMs in labeled graphs.
  • Improve seed generation for alignment methods on Elastic Founder Graphs.
  • Analyze the efficiency and applicability of graph-based MEM finding.

Main Methods:

  • Introduced an O(n d L + |output|) time algorithm for finding k-MEMs spanning L nodes.
  • Developed a k-MEM finding solution for indexable Elastic Founder Graphs.
  • Generalized the approach for multiple query strings.

Main Results:

  • Achieved a runtime of O(H^2 log H + |output|) for Elastic Founder Graphs.
  • Demonstrated that graph MEMs are substantially fewer than string MEMs.
  • Provided experimental validation for the developed algorithm.

Conclusions:

  • Enabled efficient seed production for alignment methods on Elastic Founder Graphs.
  • Facilitated the implementation of seed-chain-extend alignment on graphs.
  • Released open-source code for practical application.