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Chinese Academy of Sciences

Rapid Development of Next-Generation Sequencing Technology

Strategic Insights

— 1 min read

A recent study from the Chinese Academy of Sciences has explored the use of Next-Generation Sequencing (NGS) technology in genetic analysis. The researchers have developed a novel aligner, DH_Aligner, designed to quickly and accurately map DNA reads to reference sequences. The new technology has shown significant improvements in performance and accuracy, outperforming existing parallel implementations by up to 7.8 times.

Key Takeaways:

  • The rapid development of NGS technology has led to an increased demand for fast and accurate genetic analysis.
  • The researchers have proposed a novel aligner, DH_Aligner, which uses a three-phased aligning workflow: seeding-filtering-extension.
  • DH_Aligner is optimized for x86 multi-core platforms with AVX2/AVX512 SIMD instruction sets and provides an end-to-end solution for read alignment from Fastq to SAM files.
  • The algorithm uses a fast seeding scheme and a seed filtering procedure to avoid time-consuming seeding phases and redundant workload.
  • With the introduction of batched-processing methodology, parallelism is easily exploited at data-, instruction-, and thread-level.
  • The performance-critical kernels in DH_Aligner are implemented by both AVX2 and AVX512 intrinsics for improved performance and portability.
  • On two typical x86-based platforms, DH_Aligner can produce a near-best accuracy/sensitivity while outperforming state-of-the-art parallel implementations with average speedups of 7.8x, 3.4x, 2.8x-6.7x, and 1.5x over bwa-mem, bwa-mem2, bowtie2, and minimap2, respectively.
  • The research has been peer-reviewed and published in the Journal of Parallel and Distributed Computing.
  • The study highlights the potential of DH_Aligner in fast and accurate genetic analysis, which can lead to critical breakthroughs in various fields, including medicine and genetics.

Statistics:

  • Average speedup of DH_Aligner over state-of-the-art parallel implementations: 7.8x, 3.4x, 2.8x-6.7x, and 1.5x over bwa-mem, bwa-mem2, bowtie2, and minimap2, respectively.
  • Number of platforms tested: 2 (Intel Xeon-6154 and Hygon C86-7285).
  • Publication date: 2025.
  • Journal: Journal of Parallel and Distributed Computing.

Sources:

  • Dh_aligner: a Fast Short-read Aligner On Multicore Platforms With Avx Vectorization. Journal of Parallel and Distributed Computing, 2025;205.
  • Chinese Academy of Sciences. Institute of Software, Beijing 100190, People's Republic of China.
  • National Key Research & Development Program of China. Science and Technology Support Program of Guizhou Province.

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