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

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 framew...

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Detalles Bibliográficos
Autores principales: Zhang, Liubin, Yuan, Yangyang, Peng, Wenjie, Tang, Bin, Li, Mulin Jun, Gui, Hongsheng, Wang, Qiang, Li, Miaoxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10108510/
https://www.ncbi.nlm.nih.gov/pubmed/37069653
http://dx.doi.org/10.1186/s13059-023-02906-z
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02906-z.