123VCF
123VCF filters genetic variants in Variant Call Format (VCF) files generated from Next-Generation Sequencing (NGS) data to support identification of clinically relevant and disease-associated variants.
Key Features:
- VCF File Processing: Processes both compressed and uncompressed Variant Call Format (VCF) files for genomic variant analysis.
- Disk-Streaming Filtering Algorithm: Applies a disk-streaming real-time filtering algorithm to analyze large variant datasets.
- Customizable Filtering Parameters: Supports filtering based on parameters including quality scores, coverage depth, and population variant frequency.
- User-Defined Filtering Rules: Enables application of custom filtering criteria tailored to specific research or clinical case requirements.
- Java-Based Implementation: Implements variant filtering within a Java framework for processing genomic datasets.
- Algorithmic Performance Comparison: Demonstrates runtime performance comparable to BCFtools filter and GATK VariantFiltration.
Scientific Applications:
- Disease Variant Identification: Supports identification of potentially pathogenic variants from Next-Generation Sequencing datasets.
- Medical Genetics Research: Facilitates analysis of genetic variants associated with inherited and complex diseases.
- Genomic Variant Analysis: Enables filtering of large variant datasets to prioritize variants for downstream genomic and clinical studies.
Methodology:
The tool processes compressed or uncompressed VCF files using a disk-streaming real-time filtering algorithm and applies user-defined filters based on quality scores, coverage depth, and population variant frequency.
Topics
Details
- License:
- MIT
- Cost:
- Free of charge
- Tool Type:
- desktop application
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Java
- Added:
- 5/24/2024
- Last Updated:
- 5/24/2024
Operations
Data Inputs & Outputs
Publications
Eidi M, Abdolalizadeh S, Moeini S, Garshasbi M, Zahiri J. 123VCF: an intuitive and efficient tool for filtering VCF files. BMC Bioinformatics. 2024;25(1). doi:10.1186/s12859-024-05661-5. PMID:38350858. PMCID:PMC10865685.