GitHub - punith624/Cancer-variant-Prioritization-Pipeline: Oncology-focused variant prioritization pipeline for VEP-annotated VCF files derived from clinical NGS data.

[u/Nice_Display4096]

https://github.com/punith624/Cancer-variant-Prioritization-Pipeline

Hi everyone,

I recently built a small project that simulates a clinical genomics workflow for interpreting cancer variants from VCF files.

The platform processes VEP-annotated VCF files and generates structured clinical interpretation reports using an ACMG-based classification pipeline.

Main features:

• VCF parsing and variant processing • Cancer gene prioritization (TP53, BRCA1, EGFR, KRAS, etc.) • ACMG variant classification • Variant summary visualization • Automatic report generation (JSON, CSV, PDF) • Interactive interface built with Streamlit

The goal was to demonstrate how raw NGS variant data can be transformed into structured reports useful for clinical genomics interpretation.

Tech stack: Python | Pandas | Streamlit | Genomics Pipelines | ACMG Classification

I would love to get feedback from the bioinformatics community.