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Related Experiment Video

Updated: May 16, 2025

Competitive Genomic Screens of Barcoded Yeast Libraries
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The small genomics lab experience optimizing data cold storage.

Elisha D O Roberson1

  • 1Washington University in St. Louis, Departments of Medicine & Genetics, Division of Rheumatology, St. Louis, MO 63110.

Biorxiv : the Preprint Server for Biology
|April 1, 2025
PubMed
Summary
This summary is machine-generated.

Genomics labs can save over 20% on cold storage costs by using zstandard compression for FASTQ files instead of gzip. This data compression method is efficient for long-term storage needs.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Data Storage

Background:

  • Translational research requires collaboration between basic scientists, clinicians, and genomics/bioinformatics experts.
  • While data generation is supported by core facilities, long-term data storage often burdens individual researchers.
  • FASTQ file storage is a common responsibility for collaborative genomics labs.

Purpose of the Study:

  • To evaluate the effectiveness of different compression algorithms for long-term FASTQ file storage.
  • To identify methods for reducing cold storage space requirements in collaborative genomics research.

Main Methods:

  • Comparison of space savings between gzip and zstandard compression algorithms.
  • Testing on an existing dataset of FASTQ files to assess compression ratios.

Main Results:

  • Zstandard achieved a better overall compression ratio compared to the optimal gzip algorithm.
  • Utilizing zstandard resulted in over 20% space savings for FASTQ files.

Conclusions:

  • Zstandard compression offers significant space savings for FASTQ files.
  • Transitioning to zstandard is recommended for small, collaborative genomics labs to minimize cold storage costs.