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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

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

Liubin Zhang^1,2,3, Yangyang Yuan^1,2,3,4, Wenjie Peng^1,2,3

¹Program in Bioinformatics, Zhongshan School of Medicine and The Fifth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.

|April 18, 2023

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:

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

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