myVCF
myVCF organizes VCF files into an SQLite database and provides querying, summary statistics, and export of genetic variants and sample genotypes to support interpretation of next-generation sequencing data.
Key Features:
- Efficient Data Management: Organizes data from VCF (Variant Call Format) files into a structured SQLite database, supporting multiple sequencing projects and storing genetic variants and sample genotypes.
- Flexible Search Engine: Enables queries by chromosomal regions, specific genes, individual variants, and dbSNP IDs.
- Data Visualization and Reporting: Generates summary statistics reports that aggregate information from VCF files to characterize mutation distributions across samples and genomic/exomic regions and aid functional interpretation of variants.
- Export Functionality: Exports mutation data for downstream analysis and integration with other bioinformatics tools.
Scientific Applications:
- Variant discovery and disease association: Facilitates discovery and interpretation of genetic variants associated with human diseases using next-generation sequencing data.
- Functional analysis of variants: Supports aggregation and reporting required for functional analysis of genetic variations in wet-lab research.
- Translational and clinical research: Provides variant data management and summaries to support variant interpretation in clinical and translational research contexts.
Methodology:
Ingests VCF files and loads variant and genotype records into an SQLite database, supports indexed queries by chromosomal region/gene/variant/dbSNP ID, generates summary statistics and mutation distribution reports from aggregated VCF information, and exports mutation datasets.
Topics
Details
- Tool Type:
- desktop application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Python
- Added:
- 6/16/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Pietrelli A, Valenti L. myVCF: a desktop application for high-throughput mutations data management. Bioinformatics. 2017;33(22):3676-3678. doi:10.1093/bioinformatics/btx475. PMID:29036298.
PMID: 29036298