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Related Concept Videos

Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

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Introductory Analysis and Validation of CUT&RUN Sequencing Data
04:58

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

High-throughput compression of FASTQ data with SeqDB.

Mark Howison1

  • 1Center for Computation and Visualization, Brown University, Providence, RI 02912, USA. mhowison@brown.edu

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|May 25, 2013
PubMed
Summary
This summary is machine-generated.

Next-generation sequencing (NGS) data compression is crucial. SeqDB offers high-throughput compression for NGS data, combining Blosc and a new SeqPack scheme to overcome I/O bottlenecks.

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Area of Science:

  • Bioinformatics
  • Data Compression
  • High-Performance Computing

Background:

  • Next-generation sequencing (NGS) data storage faces challenges due to rapidly increasing data volumes.
  • Current compression methods prioritize compression ratio over throughput, creating I/O bottlenecks.
  • Low throughput of compression methods limits the performance of analyses on high-performance computing systems.

Purpose of the Study:

  • To introduce SeqDB, a novel storage model for high-throughput compression of NGS data.
  • To address the performance limitations of existing sequence data compression techniques.
  • To achieve high compression throughput with minimal impact on compression ratios.

Main Methods:

  • Development of SeqDB, a new storage model for sequence data.
  • Integration of the multithreaded Blosc compressor.
  • Implementation of SeqPack, a novel data-parallel byte-packing scheme that interleaves sequence and quality score data.

Main Results:

  • SeqDB provides high-throughput compression for next-generation sequencing data.
  • The SeqPack scheme effectively interleaves sequence and quality score data for efficient packing.
  • Minimal sacrifice in compression ratio is observed while significantly improving throughput.

Conclusions:

  • SeqDB offers a viable solution to the throughput limitations in NGS data compression.
  • The proposed SeqPack scheme enhances compression efficiency for sequence and quality data.
  • SeqDB is well-suited for high-performance computing environments demanding efficient data handling.