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Efficient Acceleration of the Pair-HMMs Forward Algorithm for GATK HaplotypeCaller on Graphics Processing Units.

Shanshan Ren1, Koen Bertels1, Zaid Al-Ars1

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Summary

This study accelerates the pair-Hidden Markov Models (HMMs) forward algorithm on graphics processing units (GPUs) to speed up GATK HaplotypeCaller (HC) variant detection. GPU implementations achieved up to 5.47× speedup, improving performance for complex genome analysis.

Keywords:
GATK HaplotypeCallerGPU accelerationPair-HMMs forward algorithmmemory access

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • GATK HaplotypeCaller (HC) is crucial for variant identification in complex genomes.
  • Its high accuracy is offset by long execution times, primarily due to the pair-Hidden Markov Models (HMMs) forward algorithm.

Purpose of the Study:

  • To accelerate the pair-HMMs forward algorithm using graphics processing units (GPUs).
  • To enhance the overall performance of GATK HaplotypeCaller (HC).

Main Methods:

  • Developed and implemented several GPU-based versions of the pair-HMMs forward algorithm.
  • Analyzed performance bottlenecks on an NVIDIA Tesla K40 GPU with diverse datasets.

Main Results:

  • Identified optimal GPU implementations for various datasets based on performance analysis.
  • Achieved significant speedups, reaching up to 5.47× compared to existing GPU implementations.

Conclusions:

  • GPU acceleration of the pair-HMMs forward algorithm effectively improves GATK HC performance.
  • The optimized GPU implementations offer substantial speedups for variant calling in complex genomes.