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.