VarWatch
VarWatch matches and monitors genetic variants, especially variants of unknown significance (VUS) identified by high-throughput sequencing, to support variant interpretation and case aggregation.
Key Features:
- Variant matching and registration: Registers VUS and identifies potential matches to other case descriptions by comparing entries within its register and against external databases.
- Continuous monitoring: Continuously monitors registered variants to detect new matches or additional evidence relevant to variant interpretation.
- Cross-referencing: Cross-references case descriptions with external databases and an internal register to facilitate discovery of comparable cases.
- Programmatic tools: Provides programmatic tools to perform internal case matching and automated comparison workflows.
- Scalability: Designed to scale to large consortia of diagnostic laboratories and collaborative data producers.
Scientific Applications:
- Gene-based diagnosis: Enables genome-wide detection and evaluation of putatively causative mutations from high-throughput sequencing for inherited human diseases.
- Case aggregation: Facilitates discovery of comparable case reports to support individual patient diagnoses.
- Clinical interpretation of VUS: Supports assessment and re-evaluation of the clinical relevance of variants of unknown significance.
Methodology:
Registers and continuously monitors VUS, cross-references cases against external databases and an internal register, and performs internal case matching while accommodating privacy and legal constraints such as the General Data Protection Regulation (EU-2016/679).
Topics
Collections
Details
- Tool Type:
- command-line tool
- Programming Languages:
- Java
- Added:
- 1/20/2021
- Last Updated:
- 5/21/2021
Operations
Publications
Fredrich B, Schmöhl M, Junge O, Gundlach S, Ellinghaus D, Pfeufer A, Bettecken T, Siddiqui R, Franke A, Wienker TF, Hoeppner MP, Krawczak M. VarWatch—A stand-alone software tool for variant matching. PLOS ONE. 2019;14(4):e0215618. doi:10.1371/journal.pone.0215618. PMID:31022234. PMCID:PMC6483337.