GenESysV
GenESysV facilitates exploration and management of genomic variants generated by high-throughput sequencing to store, prioritize, and retrieve candidate disease-causing variants for studies of Mendelian and complex human disorders.
Key Features:
- Scalability and performance: Handles datasets from a few samples to thousands while maintaining rapid data importation and efficient query performance.
- Variant storage and management: Stores, organizes, and retrieves genomic variants produced by high-throughput sequencing and genotyping projects.
- Variant prioritization: Enables prioritization of candidate disease-causing variants following variant calling.
- Applicability across project types: Supports analyses for diverse high-throughput sequencing and genotyping projects.
- Support for Mendelian and complex disease studies: Applicable to discovery and analysis workflows for both Mendelian and complex human disorders.
- Secure data access: Incorporates mechanisms to control access to sensitive genomic data.
Scientific Applications:
- Candidate variant discovery: Narrows down candidate disease-causing variants from large high-throughput sequencing datasets.
- Mendelian disease research: Supports identification and documentation of variants underlying Mendelian disorders.
- Complex disease genetics: Facilitates exploration of variant contributions to complex human diseases.
- Basic and clinical genomics: Serves both basic genetic research and clinical genomics applications.
Methodology:
Integrates data storage, management, prioritization, retrieval, and optimized data import and query performance for variant datasets.
Topics
Details
- License:
- GPL-2.0
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- api
- Operating Systems:
- Linux, Mac
- Programming Languages:
- Java, Python
- Added:
- 5/22/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Zia M, Spurgeon P, Levesque A, Furlani T, Wang J. GenESysV: a fast, intuitive and scalable genome exploration open source tool for variants generated from high-throughput sequencing projects. BMC Bioinformatics. 2019;20(1). doi:10.1186/s12859-019-2636-5. PMID:30704396. PMCID:PMC6357466.