Published in

BioMed Central, Genome Biology, 1(24), 2023

DOI: 10.1186/s13059-023-02906-z

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

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

AbstractWhole -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.