How does the skill handle large data files?

The included Python scripts are designed to handle multi-GB downloads with progress tracking and support for compressed formats like .gz for efficient storage.

Which genome assemblies does the cosmic-database skill support?

The skill supports both GRCh38 (current standard) and GRCh37 (legacy) reference genomes.

Is this skill suitable for commercial oncology research?

While the skill provides the technical interface, commercial use of COSMIC data requires a valid license from QIAGEN/Sanger Institute.

Do I need a COSMIC account to use this skill?

Yes, COSMIC requires authentication. Academic users can register for free at the COSMIC website, while commercial users require a license from QIAGEN.

Can I download specific mutation types like gene fusions?

Yes, the skill allows you to download specialized datasets including gene fusions, structural variants, copy number alterations, and resistance mutations.

Cosmic Database

Name: Cosmic Database
Author: pur3v4d3r

bypur3v4d3r

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Data Science & ML

Accesses and queries the Catalogue of Somatic Mutations in Cancer (COSMIC) for precision oncology and genomic research.

About

This skill provides programmatic access to COSMIC, the world's most comprehensive resource for exploring somatic mutations in human cancer. It allows researchers and bioinformaticians to automate the download and analysis of critical datasets, including the Cancer Gene Census, mutational signatures, and drug resistance data. By integrating these scientific datasets directly into development workflows, users can efficiently filter genomic variants, identify oncogenic drivers, and build robust bioinformatics pipelines for precision medicine and cancer research.

Key Features

1 GitHub stars
Automated downloading of somatic mutation exports and VCF files
Support for both GRCh38 and GRCh37 genome assemblies
Retrieval of mutational signature profiles (SBS, DBS, and ID signatures)
Python helper functions for filtering mutations by gene, role, or cancer type
Programmatic access to the expert-curated Cancer Gene Census

Use Cases

Analyzing clinical sequencing data for known drug resistance mutations
Building automated bioinformatics pipelines for variant annotation
Identifying known cancer-driving genes and their specific roles in tumorigenesis

About

Key Features

1 GitHub stars
Automated downloading of somatic mutation exports and VCF files
Support for both GRCh38 and GRCh37 genome assemblies
Retrieval of mutational signature profiles (SBS, DBS, and ID signatures)
Python helper functions for filtering mutations by gene, role, or cancer type
Programmatic access to the expert-curated Cancer Gene Census

Use Cases

Analyzing clinical sequencing data for known drug resistance mutations
Building automated bioinformatics pipelines for variant annotation
Identifying known cancer-driving genes and their specific roles in tumorigenesis