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Gerbil: a fast and memory-efficient k-mer counter with GPU-support.

Marius Erbert1, Steffen Rechner1, Matthias Müller-Hannemann1

  • 1Institute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saae), Germany.

Algorithms for Molecular Biology : AMB
|April 5, 2017
PubMed
Summary

Gerbil is a new open-source software for efficient k-mer counting in genomes, especially for large k values (≥ 32). It outperforms existing tools for large k, enabling new bioinformatics applications.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • K-mer counting is fundamental in bioinformatics.
  • Existing tools struggle with large k-values (≥ 32) and high memory usage.
  • Next-generation sequencing trends necessitate efficient large k-mer counting.

Purpose of the Study:

  • Introduce Gerbil, an open-source k-mer counting software.
  • Address the limitations of current tools for large k-values.
  • Provide efficient k-mer counting for both small and large k.

Main Methods:

  • Gerbil employs a two-step approach: data redistribution and hash table-based counting.
  • The software is optimized through intensive algorithm engineering.
  • Optional GPU acceleration is available for the counting step.
Keywords:
Algorithm engineeringGPU computingGenome sequencesde novo assemblyk-mer counting

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Main Results:

  • Gerbil efficiently counts k-mers for both small (k < 32) and large (k ≥ 32) values.
  • Performance is comparable to existing tools for small k.
  • Gerbil significantly outperforms competitors for large k.

Conclusions:

  • Gerbil enables new bioinformatics applications requiring large k-values.
  • It offers a scalable and efficient solution for large k-mer counting.
  • The software provides a valuable tool for modern genomic analysis.