Which genome assemblies are supported?

The skill supports both GRCh38 (the current recommended standard) and GRCh37 (legacy) assemblies.

How often is the data updated?

COSMIC is typically updated on a quarterly basis. The skill defaults to the 'latest' version but allows you to specify specific releases (e.g., v101) for scientific reproducibility.

Does this skill require a COSMIC account?

Yes, you must register for an account at the COSMIC website. Access is free for academic users but requires a commercial license for corporate use.

Can I use this for large-scale data analysis?

Yes, the skill provides Python scripts to download large TSV and VCF files, which can then be processed efficiently using libraries like pandas, pysam, or Dask.

Cosmic Cancer Database Access

Name: Cosmic Cancer Database Access
Author: ricable

byricable

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Data Science & ML

Access and query the COSMIC database for somatic mutations, cancer gene census, and mutational signatures to support precision oncology research.

About

This skill integrates the COSMIC (Catalogue of Somatic Mutations in Cancer) database directly into your AI-assisted workflow, enabling researchers and bioinformaticians to programmatically retrieve comprehensive cancer genomics data. It provides streamlined access to millions of somatic mutations, the expert-curated Cancer Gene Census, and mutational signatures across both GRCh37 and GRCh38 assemblies. Whether you are identifying drug resistance markers, analyzing gene fusions, or building bioinformatics pipelines, this skill automates the complex authentication and download processes required to work with high-quality oncology data.

Key Features

Support for both GRCh37 and GRCh38 human genome assemblies
Python-based integration for processing data with Pandas and Pysam
Access to specialized datasets including mutational signatures, gene fusions, and resistance mutations
Programmatic handling of COSMIC authentication and quarterly release updates
Automated retrieval of somatic mutation and Cancer Gene Census (CGC) data
1 GitHub stars

Use Cases

Identifying oncogenes and tumor suppressors for targeted gene panels
Extracting mutational signature profiles for tumor etiology analysis
Filtering variant call files (VCFs) against known cancer driver mutations

About

Key Features

Support for both GRCh37 and GRCh38 human genome assemblies
Python-based integration for processing data with Pandas and Pysam
Access to specialized datasets including mutational signatures, gene fusions, and resistance mutations
Programmatic handling of COSMIC authentication and quarterly release updates
Automated retrieval of somatic mutation and Cancer Gene Census (CGC) data
1 GitHub stars

Use Cases

Identifying oncogenes and tumor suppressors for targeted gene panels
Extracting mutational signature profiles for tumor etiology analysis
Filtering variant call files (VCFs) against known cancer driver mutations