Recommended Citation
Zhang L, Yuan Y, Peng W, Tang B, Li MJ, Gui H, Wang Q, and Li M. GBC: a parallel toolkit based on highly addressable byte-encoding blocks for extremely large-scale genotypes of species. Genome Biol 2023; 24(1):76.
Document Type
Article
Publication Date
4-17-2023
Publication Title
Genome biology
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.
Medical Subject Headings
Humans; Software; Algorithms; Genotype; Data Compression; Genomics
PubMed ID
37069653
Volume
24
Issue
1
First Page
76
Last Page
76
