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.