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Related Experiment Videos

AQUa: an adaptive framework for compression of sequencing quality scores with random access functionality.

Tom Paridaens1, Glenn Van Wallendael1, Wesley De Neve1,2,3

  • 1Department of Electronics and Information Systems, IDLab, Ghent University - IMEC, Ghent, Belgium.

Bioinformatics (Oxford, England)
|October 14, 2017
PubMed
Summary

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New lossless compression framework AQUa significantly reduces genomic data file sizes, offering up to 38.49% reduction compared to Gzip. This technology addresses the challenge of exponentially increasing genomic data storage and transmission needs.

Area of Science:

  • Bioinformatics
  • Genomic Data Compression

Background:

  • Genome sequencing costs have decreased, leading to exponential growth in genomic data.
  • Efficient storage and transmission of large genomic datasets are critical challenges.

Purpose of the Study:

  • Introduce AQUa, an adaptive framework for lossless compression of quality scores.
  • Mitigate storage and transmission issues associated with large-scale genomic data.

Main Methods:

  • Utilizes a configurable set of coding tools.
  • Incorporates a Context-Adaptive Binary Arithmetic Coding scheme.
  • Framework supports random access.

Main Results:

  • Achieved file size reductions of up to 38.49% compared to GNU Gzip.

Related Experiment Videos

  • Reduced file sizes by up to 6.48% compared to 7-Zip (Ultra Setting).
  • Outperformed single-pass compressor SCALCE by up to 21.14%, while retaining random access support.

    • Conclusions:

    • AQUa provides an effective solution for lossless compression of genomic quality scores.
    • The framework offers competitive compression ratios while maintaining random access capabilities.
    • This work aligns with ongoing efforts in genomic information representation (MPEG-G).