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GASAL2: a GPU accelerated sequence alignment library for high-throughput NGS data.

Nauman Ahmed1, Jonathan Lévy2, Shanshan Ren2

  • 1Delft University of Technology, Delft, Netherlands and University of Engineering and Technology, Lahore, Pakistan. n.ahmed@tudelft.nl.

BMC Bioinformatics
|October 27, 2019
PubMed
Summary
This summary is machine-generated.

GASAL2 is a new GPU library for DNA and RNA sequence alignment that significantly outperforms existing CPU and GPU solutions. This accelerated library enhances next-generation sequencing (NGS) data analysis speed and efficiency.

Keywords:
GPU libraryGenomicsNGSSequence alignment

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Sequence alignment is computationally intensive, necessitating accelerated solutions.
  • Existing GPU libraries like NVBIO offer limited performance for high-throughput next-generation sequencing (NGS) data.
  • There is a need for more efficient GPU-accelerated sequence alignment tools.

Purpose of the Study:

  • To introduce GASAL2, a novel GPU library for DNA and RNA sequence alignment.
  • To demonstrate GASAL2's superior performance compared to existing CPU and GPU alignment libraries.
  • To showcase GASAL2's potential for accelerating bioinformatics workflows.

Main Methods:

  • Development of specialized, accelerated GPU kernels for local, global, and semi-global sequence alignment.
  • Implementation of GPU-based sequence packing for enhanced efficiency.
  • Asynchronous/non-blocking API design for CPU and GPU execution overlap.
  • Integration and evaluation of GASAL2 within the BWA-MEM algorithm.

Main Results:

  • GASAL2 outperforms leading CPU-optimized libraries (SeqAn, Parasail) and the GPU library NVBIO.
  • GPU-based sequence packing in GASAL2 is up to 750x faster than NVBIO.
  • GASAL2 achieves up to 21x speedup over Parasail and 13x over NVBIO on a GTX 1080 Ti GPU.
  • Integration with BWA-MEM resulted in a 20x speedup in local alignment and a 1.3x overall application speedup.

Conclusions:

  • GASAL2 offers high-performance APIs for various alignment types, suitable for integration into bioinformatics tools.
  • The library significantly accelerates DNA and RNA sequence alignment on GPUs.
  • GASAL2 represents a substantial advancement in efficient NGS data analysis.