GBC: a parallel toolkit based on highly addressable byte-encoding blocks for extremely large-scale genotypes of species

Abstract

Abstract Whole -genome sequencing projects of millions of subjects contain enormous genotypes, entailing a huge memory burden and time for computation. Here, we present GBC, a toolkit for rapidly compressing large-scale genotypes into highly addressable byte-encoding blocks under an optimized parallel framework. We demonstrate that GBC is up to 1000 times faster than state-of-the-art methods to access and manage compressed large-scale genotypes while maintaining a competitive compression ratio. We also showed that conventional analysis would be substantially sped up if built on GBC to access genotypes of a large population. GBC’s data structure and algorithms are valuable for accelerating large-scale genomic research.

Keywords

• Large-scale genotypes
• Genotype compression
• Highly addressable genotype blocks
• Byte-encoding genotypes
• Genotype management
• Parallelization algorithm