GBC

GBC compresses large-scale genotypes from whole-genome sequencing projects into highly addressable byte-encoding blocks to reduce memory burden and accelerate data access for analyses involving millions of subjects.


Key Features:

  • High-Speed Compression: Implements compression and access routines reported to be up to 1000-fold faster than existing state-of-the-art methods for large-scale genotype access.
  • Optimized Parallel Framework: Uses an optimized parallel framework to reduce computational time and scale compression across extensive genotype datasets.
  • Competitive Compression Ratio: Maintains a competitive compression ratio while preserving data integrity to minimize storage requirements.
  • Enhanced Data Accessibility: Structures genotypes into highly addressable byte-encoding blocks to enable rapid retrieval and downstream analysis on large populations.

Scientific Applications:

  • Accelerating large-scale genomic research: Enables rapid access to genotypes to accelerate analyses in studies involving millions of subjects.
  • Population genetics: Facilitates population genetics analyses by improving scalable storage and rapid access to genotypes.
  • Evolutionary biology: Supports evolutionary biology studies that require analysis of large cohorts by enabling efficient genotype retrieval.
  • Personalized medicine: Supports personalized medicine research by enabling rapid access to individual-level genotypes within large cohorts.

Methodology:

Applies a parallel compression strategy that transforms large-scale genotypes into highly addressable byte-encoding blocks and employs an optimized parallel framework for scalable, fast compression and retrieval.

Topics

Details

License:
BSD-3-Clause
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Java
Added:
11/10/2023
Last Updated:
11/24/2024

Operations

Publications

Zhang L, Yuan Y, Peng W, Tang B, Li MJ, Gui H, Wang Q, Li M. GBC: a parallel toolkit based on highly addressable byte-encoding blocks for extremely large-scale genotypes of species. Genome Biology. 2023;24(1). doi:10.1186/s13059-023-02906-z. PMID:37069653. PMCID:PMC10108510.

PMID: 37069653
Funding: - National Natural Science Foundation of China: 31771401, 31970650

Documentation

Links