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High-throughput sequencing relies on the FASTQ format. A new multi-threaded Pseudogenome-based Read Compressor (PgRC) improves compression and decompression speeds for DNA sequences without sacrificing the compression ratio.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • The FASTQ format is fundamental for storing high-throughput sequencing data.
  • Existing specialized FASTQ compressors face practical performance limitations.
  • Efficient compression of large sequencing datasets is crucial for storage and analysis.

Purpose of the Study:

  • To present a multi-threaded version of the Pseudogenome-based Read Compressor (PgRC).
  • To improve the practical performance of DNA sequence compression.
  • To maintain or enhance compression ratios while reducing processing time.

Main Methods:

  • Developed a multi-threaded implementation of the PgRC algorithm.
  • Utilized an in-memory approach for compressing DNA streams.
  • Employed an approximation of the shortest common superstring for high-quality reads.
  • Implemented efficient redundancy removal using a compact temporary representation.

Main Results:

  • The multi-threaded PgRC (v2.0) maintains the compression ratio of the previous version.
  • Achieved an 8-9 fold reduction in compression time.
  • Achieved a 2-2.5 fold reduction in decompression time on a 14-core/28-thread machine.
  • Demonstrated significant speed improvements for DNA sequence compression.

Conclusions:

  • The multi-threaded PgRC offers a practical solution for compressing FASTQ data.
  • PgRC v2.0 significantly enhances the efficiency of DNA sequence compression.
  • This advancement addresses performance tradeoffs in existing FASTQ compressors.
  • The tool is available for download, facilitating its adoption in high-throughput sequencing workflows.