How does this skill help with VCF annotation?

It provides specific command-line examples and code snippets using tools like bcftools and Python to map ClinVar clinical significance data onto your existing genomic variant call sets.

Can I use this for real-time clinical diagnosis?

No, this skill is intended for research and development purposes. Clinical interpretations should always be performed or verified by a qualified genetics professional.

Does it support both GRCh37 and GRCh38 genome builds?

Yes, the skill includes documentation and instructions for accessing and processing ClinVar data for both the GRCh37 and GRCh38 reference genomes.

How does it handle NCBI API rate limits?

The skill outlines best practices such as using API keys to increase request limits and implementing exponential backoff strategies to ensure stable programmatic access.

ClinVar Database Integration

Name: ClinVar Database Integration
Author: Activer007

byActiver007

Data Science & ML

Queries the NCBI ClinVar database to identify genetic variants, interpret pathogenicity classifications, and annotate genomic data for bioinformatics pipelines.

About

The ClinVar Database skill enables bioinformaticians and researchers to interact efficiently with NCBI's archive of human genetic variants and their relationships to phenotypes. It provides specialized guidance for querying clinical significance via web and E-utilities API interfaces, processing bulk data in XML and VCF formats, and interpreting standardized ACMG/AMP pathogenicity classifications. This skill is essential for building genomic medicine pipelines, resolving conflicting variant interpretations, and automating the annotation of variant call sets with up-to-date clinical evidence within the Claude environment.

Key Features

Programmatic access via NCBI E-utilities API
Bulk data processing for VCF, XML, and tab-delimited files
0 GitHub stars
Variant annotation workflows using bcftools and Python
Conflict resolution strategies for variant classification
Standardized ACMG/AMP pathogenicity interpretation guidance

Use Cases

Filtering high-confidence pathogenic variants in specific disease-related genes
Automating the construction of local bioinformatic databases from monthly ClinVar releases
Annotating VCF files with clinical significance for genomic research pipelines

About

Key Features

Programmatic access via NCBI E-utilities API
Bulk data processing for VCF, XML, and tab-delimited files
0 GitHub stars
Variant annotation workflows using bcftools and Python
Conflict resolution strategies for variant classification
Standardized ACMG/AMP pathogenicity interpretation guidance

Use Cases

Filtering high-confidence pathogenic variants in specific disease-related genes
Automating the construction of local bioinformatic databases from monthly ClinVar releases
Annotating VCF files with clinical significance for genomic research pipelines