G-FQZip: Lossless Reference-Based Compression of FASTQ Files Using GPUs

摘要

The exponentially increasing high throughput of sequencing data calls for efficient specific compression methods to address the challenges posed by the storage and transmission of such data. In this work, we develop a GPU version of lossless reference-based compression method namely G-FQZip by introducing a GPU-based arithmetic coding, a template matching approach, and a parallel light-weight mapping model. The comparison experiments demonstrate that G-FQZip can improve the (de) compression speed while maintaining comparable compression ratios. Besides, the follow-up evaluation demonstrated the efficiency of the GPU-based arithmetic coding and the template matching approach.