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.