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Improving transmission efficiency of large sequence alignment/map (SAM) files.

Muhammad Nazmus Sakib1, Jijun Tang, W Jim Zheng

  • 1Department of Computer Science & Engineering, University of South Carolina, Columbia, South Carolina, United States of America.

Plos One
|December 14, 2011
PubMed
Summary
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SAMZIP offers improved lossless compression for genomic sequence alignment data. This specialized encoding scheme reduces file size, significantly decreasing data transmission times for bioinformatics research.

Area of Science:

  • Bioinformatics
  • Genomic Data Analysis
  • Computational Biology

Background:

  • Bioinformatics research relies heavily on collecting and analyzing vast amounts of genomic data.
  • Efficient storage and transfer of large genomic datasets are critical challenges.
  • Lossless compression techniques are essential for reducing the transmission time of large sequencing data files.

Purpose of the Study:

  • To present SAMZIP, a novel encoding scheme for sequence alignment data.
  • To enhance the compression ratio of existing compression tools for SAM format files.
  • To reduce the overall data transmission time in bioinformatics workflows.

Main Methods:

  • Developed a specialized encoding scheme, SAMZIP, tailored for Sequence Alignment/Map (SAM) format.

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  • Leveraged prior knowledge of the SAM file format and its specifications to optimize compression.
  • Conducted experimental evaluations to assess compression performance against existing tools.

    • Main Results:

    • SAMZIP significantly improves the compression ratio for sequence alignment data.
    • The proposed encoding scheme outperforms existing compression tools in terms of file size reduction.
    • Experimental results demonstrate a substantial decrease in overall data transmission time.

    Conclusions:

    • SAMZIP provides an effective solution for compressing large genomic sequence alignment files.
    • The specialized encoding approach offers a notable improvement in data compression efficiency.
    • Reduced transmission times facilitated by SAMZIP can accelerate bioinformatics research and data sharing.