Local Python Tool for VCF Annotation (Offline)

We need a fully offline Python application to annotate VCF files from whole-exome sequencing. The tool should use either ANNOVAR or VEP for variant consequences, reference local gnomAD and ClinVar databases for allele frequencies and clinical significance, and output an annotated CSV or TSV file. Key Requirements - Must run locally without internet connectivity. - Incorporate local gnomAD and ClinVar data (no external API calls). - Support ANNOVAR or Ensembl VEP (developer can recommend which is more suitable for a fully offline workflow). - Capture essential variant details, including gene/transcript info, predicted impact, and any other relevant annotations from the chosen tool. Input/Output - Input: Standard whole-exome VCF file(s). - Output: Annotated variant file in CSV or TSV. Local Databases - Use local copies of gnomAD (population allele frequencies) and ClinVar (clinical significance). - Provide guidance/documentation on how to update these databases as needed. Testing - We have sample VCF files for internal testing. - The final solution should be validated on these files to ensure correct, complete annotations. Internal Use Only - No distribution beyond our organization. - Code ownership and confidentiality are important. Deliverables & Documentation - Well-documented Python code (compatible with Python 3.8+). - Clear instructions for installation and usage (e.g., README, setup scripts). - Explanation of how to refresh or replace the local gnomAD/ClinVar data. Performance & Scalability - Should efficiently process typical exome-scale VCF files with minimal run times. - Memory footprint and runtime should be appropriate for a desktop or basic server environment.