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LFastqC: A lossless non-reference-based FASTQ compressor.

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  • 1Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, United States of America.

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|November 15, 2019
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Summary
This summary is machine-generated.

A new lossless compression algorithm, LFastqC, efficiently compresses next-generation sequencing (NGS) data. It offers superior compression ratios and faster speeds compared to existing tools, reducing storage and transmission costs for genomic research.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomic Data Management

Background:

  • Next-generation sequencing (NGS) generates vast amounts of redundant raw data.
  • Efficient storage and transmission infrastructures are crucial for managing genomic data.
  • High costs associated with data storage and bandwidth necessitate effective compression methods.

Purpose of the Study:

  • To introduce LFastqC, a novel lossless, non-reference-based FASTQ compression algorithm.
  • To improve upon existing compression tools like LFQC for genomic data.
  • To reduce the costs of storage space and transmission bandwidth for NGS data.

Main Methods:

  • Development of LFastqC, a lossless, non-reference-based compression algorithm for FASTQ files.
  • Comparative analysis of LFastqC against state-of-the-art compression algorithms.
  • Evaluation using diverse datasets including LS454, PacBio, and MinION.

Main Results:

  • LFastqC achieves superior compression ratios on LS454, PacBio, and MinION datasets.
  • LFastqC demonstrates improved compression and decompression speeds compared to LFQC.
  • The algorithm offers significant advantages over previously top-performing compression tools.

Conclusions:

  • LFastqC provides an effective solution for compressing large-scale NGS data.
  • The algorithm enhances efficiency and reduces costs in genomic data management.
  • LFastqC is a valuable tool for researchers dealing with substantial genomic datasets.