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copMEM2: robust and scalable maximum exact match finding.

Szymon Grabowski1, Wojciech Bieniecki1

  • 1Institute of Applied Computer Science, Lodz University of Technology, 18 Stefanowskiego Street, Lodz, Poland.

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Summary
This summary is machine-generated.

copMEM2 efficiently finds Maximum Exact Matches (MEMs) between highly similar genomes. This tool significantly speeds up genomic comparisons, outperforming existing methods for human and mouse genome analysis.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Maximum Exact Matches (MEMs) are crucial for genome-to-genome comparisons.
  • Existing tools often struggle with the computational demands of finding MEMs in very similar genomes.

Purpose of the Study:

  • To present copMEM2, an optimized, multithreaded tool for identifying MEMs.
  • To address the challenge of MEM finding in highly similar genomic data.

Main Methods:

  • Developed copMEM2 as a multithreaded implementation of its predecessor.
  • Incorporated optimizations including a predecessor query data structure and optimized sort procedures.
  • Specifically designed to handle highly similar genomic data.

Main Results:

  • Computed all MEMs (minimum length 50) between human and mouse genomes in 59 seconds using 10.40 GB RAM and 12 threads.
  • Achieved performance at least several times faster than main competing tools.
  • Processed a pair of human genomes (hg18 and hg19) in 324 seconds using 16.57 GB RAM.

Conclusions:

  • copMEM2 offers a significant speed improvement for MEM finding in large-scale genomic comparisons.
  • The tool is particularly effective for analyzing highly similar genomes, such as different human genome versions.
  • copMEM2 provides a computationally efficient solution for essential bioinformatics tasks.