What does the Alterlab Cosmic AI skill do?

Access the COSMIC catalogue of somatic mutations in cancer to query somatic mutations, the Cancer Gene Census, mutational signatures, and gene fusions (authentication required). Use when curating known cancer driver genes, looking up recurrent somatic mutations in a gene, or interpreting mutational signatures for cancer research and precision oncology. Not for germline pathogenicity calls (use alterlab-clinvar) or interactive cohort visualization like OncoPrints and survival from study data (use alterlab-cbioportal). Part of the AlterLab Academic Skills suite.

Why use Alterlab Cosmic on TypingMind?

Because you install it once and use it with any model. Alterlab Cosmic is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Alterlab Cosmic in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/databases/alterlab-cosmic. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Alterlab Cosmic?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Alterlab Cosmic?

As many as you like. As long as a model supports skills, you can use Alterlab Cosmic with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Alterlab Cosmic AI skill free?

Yes. It is published on GitHub by AlterLab-IEU under the MIT license. You only pay your own AI provider for the tokens you use.

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Alterlab Cosmic by AlterLab-IEU — AI Skill for Any LLM

COSMIC Database

Overview

COSMIC (Catalogue of Somatic Mutations in Cancer) is the world's largest and most comprehensive database for exploring somatic mutations in human cancer. Access COSMIC's extensive collection of cancer genomics data, including millions of mutations across thousands of cancer types, curated gene lists, mutational signatures, and clinical annotations programmatically.

When to Use This Skill

This skill should be used when:

Downloading cancer mutation data from COSMIC
Accessing the Cancer Gene Census for curated cancer gene lists
Retrieving mutational signature profiles
Querying structural variants, copy number alterations, or gene fusions
Analyzing drug resistance mutations
Working with cancer cell line genomics data
Integrating cancer mutation data into bioinformatics pipelines
Researching specific genes or mutations in cancer contexts

Does NOT Trigger

Scenario	Use Instead
Germline variant pathogenicity (ACMG/AMP, ClinVar stars)	`alterlab-clinvar`
Mutation frequency / OncoPrint / survival in TCGA or MSK cohorts via a keyless API	`alterlab-cbioportal`
CRISPR/RNAi gene dependency in cancer cell lines	`alterlab-depmap`
Population allele frequencies in non-cancer cohorts	`alterlab-gnomad`

Prerequisites

Account Registration

COSMIC requires authentication for data downloads:

Academic users: Free access with registration at https://cancer.sanger.ac.uk/cosmic/register
Commercial users: A COSMIC commercial licence is required for commercial R&D, products/services, and patient services or clinical reporting — see https://www.cosmickb.org/licensing

Python Requirements

bash
uv pip install requests pandas
# pysam is only needed if you read the VCF-format downloads
uv pip install pysam

Quick Start

COSMIC's current download service delivers each product as a .tar archive (the gzipped TSV or VCF plus a README describing every column) at an explicit release path, e.g. grch38/cosmic/v104/Cosmic_GenomeScreensMutant_Tsv_v104_GRCh38.tar. Scripted downloads are a two-step call: GET https://cancer.sanger.ac.uk/api/mono/products/v1/downloads/scripted?path=<archive path>&bucket=downloads with HTTP Basic auth (email:password) returns JSON with a signed url, which you then fetch without auth. The legacy /cosmic/file_download/... endpoint and legacy names such as CosmicMutantExport.tsv.gz or cancer_gene_census.csv no longer work for scripts — the old endpoint now redirects to the login page.

1. Basic File Download

Use the scripts/download_cosmic.py script to download COSMIC data files:

python
from scripts.download_cosmic import download_cosmic_file, get_common_file_path

# Cancer Gene Census, current release (v104), GRCh38
download_cosmic_file(
    email="your_email@institution.edu",
    password="your_password",
    filepath=get_common_file_path("gene_census"),
    # = "grch38/cosmic/v104/Cosmic_CancerGeneCensus_Tsv_v104_GRCh38.tar"
)

2. Command-Line Usage

bash
# Download using shorthand data type (prompts for the password)
python scripts/download_cosmic.py user@email.com --data-type mutations

# Download a specific archive path
python scripts/download_cosmic.py user@email.com \
    --filepath grch38/cosmic/v104/Cosmic_CancerGeneCensus_Tsv_v104_GRCh38.tar

# GRCh37 and/or a pinned release
python scripts/download_cosmic.py user@email.com \
    --data-type gene_census --assembly GRCh37 --version v103

If the scripted endpoint changes, copy the command shown under Scripted download for any file on https://cancer.sanger.ac.uk/cosmic/download/cosmic and set COSMIC_SCRIPTED_URL.

3. Working with Downloaded Data

bash
tar -xf Cosmic_CancerGeneCensus_Tsv_v104_GRCh38.tar   # -> gzipped TSV + README

python
import glob
import pandas as pd

# Column names differ from the legacy exports — check the README in each archive.
gene_census = pd.read_csv(glob.glob("Cosmic_CancerGeneCensus*GRCh38*.tsv.gz")[0], sep="\t")
print(gene_census.columns.tolist())

# VCF products (e.g. VCF/Cosmic_GenomeScreensMutant_Vcf_...) extract to .vcf.gz files
import pysam
vcf = pysam.VariantFile(glob.glob("Cosmic_GenomeScreensMutant*_GRCh38.vcf.gz")[0])

Available Data Types

Every data type downloads through the same download_cosmic_file(...) call shown in Quick Start — only the filepath changes. Use the --data-type shortcut (CLI) or get_common_file_path(...) (Python) to build the path, or pass the filepath directly. See references/cosmic_data_reference.md for full field descriptions.

Data type	Shortcut	Archive (`grch38/cosmic/v104/…`, verified 2026-09)
Coding mutations, genome-wide screens (WGS/WES)	`mutations`	`Cosmic_GenomeScreensMutant_Tsv_v104_GRCh38.tar`
Coding mutations, targeted screens	`targeted_mutations`	`Cosmic_CompleteTargetedScreensMutant_Tsv_v104_GRCh38.tar`
Coding mutations (VCF)	`mutations_vcf`	`VCF/Cosmic_GenomeScreensMutant_Vcf_v104_GRCh38.tar`
Non-coding variants (VCF)	`non_coding_vcf`	`VCF/Cosmic_NonCodingVariants_Vcf_v104_GRCh38.tar`
Mutations in CGC genes	`mutation_census`	`Cosmic_MutantCensus_Tsv_v104_GRCh38.tar`
Cancer Gene Census	`gene_census`	`Cosmic_CancerGeneCensus_Tsv_v104_GRCh38.tar`
Resistance mutations	`resistance_mutations`	`Cosmic_ResistanceMutations_Tsv_v104_GRCh38.tar`
Structural variants / breakpoints	`structural_variants` / `breakpoints`	`Cosmic_StructuralVariants_Tsv_…` / `Cosmic_Breakpoints_Tsv_…`
Gene fusions	`fusion_genes`	`Cosmic_Fusion_Tsv_v104_GRCh38.tar`
Copy number	`copy_number`	`Cosmic_CompleteCNA_Tsv_v104_GRCh38.tar`
Gene expression	`gene_expression`	`Cosmic_CompleteGeneExpression_Tsv_v104_GRCh38.tar`
Samples / tumour classification	`sample_info` / `classification`	`Cosmic_Sample_Tsv_…` / `Cosmic_Classification_Tsv_…`
Mutational signatures	`signatures`	separate site — https://cancer.sanger.ac.uk/signatures/downloads/

Notes:

Cancer Gene Census is the expert-curated list of cancer genes; its role-in-cancer field splits oncogenes from tumor suppressors (TSG), and Tier 1/2 grades the evidence.
The old single "all coding mutations" export is now split into genome-wide and targeted-screen files; combine both for full coverage.
Mutational signatures (SBS, DBS, ID, CN, SV; current reference set v3.6, May 2026) are downloaded from the signatures site, not through the product archives.
Each product page lists sha256/md5 checksums — verify large downloads.

Working with COSMIC Data

Genome Assemblies

COSMIC provides data for two reference genomes:

GRCh38 (recommended, current standard)
GRCh37 (legacy, for older pipelines)

Specify the assembly in file paths (lower-case directory, upper-case suffix):

python
# GRCh38 (recommended)
filepath = "grch38/cosmic/v104/Cosmic_GenomeScreensMutant_Tsv_v104_GRCh38.tar"

# GRCh37 (legacy)
filepath = "grch37/cosmic/v104/Cosmic_GenomeScreensMutant_Tsv_v104_GRCh37.tar"

Versioning

Archive paths carry an explicit release (v104 = May 2026); the download service lists only versioned paths, so pin one — get_common_file_path() defaults to the current release
COSMIC ships two releases a year (May and November: v101 2024-11, v102 2025-05, v103 2025-11, v104 2026-05); check the release notes before assuming
For reproducible research, pin the release and record it alongside your results

File Formats

TSV/CSV: Tab/comma-separated, gzip compressed, read with pandas
VCF: Standard variant format, use with pysam, bcftools, or GATK
All files include headers describing column contents

Common Analysis Patterns

Current files use upper-case column names (e.g. GENE_SYMBOL, SAMPLE_NAME), while tumour site/histology live in the sample/classification tables linked by COSMIC IDs. Confirm exact names in each archive's README before filtering. For a one-off slice (one gene, primary site, or sample) the web Filtered download option avoids pulling the multi-GB files at all.

Filter mutations by gene:

python
import glob
import pandas as pd

# Extracted from Cosmic_GenomeScreensMutant_Tsv_v104_GRCh38.tar (multi-GB)
tsv = glob.glob('Cosmic_GenomeScreensMutant*GRCh38*.tsv.gz')[0]
mutations = pd.read_csv(tsv, sep='\t', low_memory=False)
tp53_mutations = mutations[mutations['GENE_SYMBOL'] == 'TP53']

Identify cancer genes by role (normalize headers, then look up the role column):

python
cgc = pd.read_csv(glob.glob('Cosmic_CancerGeneCensus*GRCh38*.tsv.gz')[0], sep='\t')
cgc.columns = cgc.columns.str.upper().str.replace(' ', '_')
role = cgc['ROLE_IN_CANCER'].fillna('')
oncogenes = cgc[role.str.contains('oncogene')]
tumor_suppressors = cgc[role.str.contains('TSG')]

Work with VCF files (GRCh38 coordinates, bgzip + tabix index required for fetch):

python
import pysam

vcf = pysam.VariantFile(glob.glob('Cosmic_GenomeScreensMutant*GRCh38*.vcf.gz')[0])
for record in vcf.fetch('17', 7668400, 7687500):  # TP53 locus, GRCh38
    print(record.id, record.ref, record.alts, record.info)

Data Reference

For comprehensive information about COSMIC data structure, available files, and field descriptions, see references/cosmic_data_reference.md. This reference includes:

Complete list of available data types and files
Detailed field descriptions for each file type
File format specifications
Common file paths and naming conventions
Data update schedule and versioning
Citation information

Use this reference when:

Exploring what data is available in COSMIC
Understanding specific field meanings
Determining the correct file path for a data type
Planning analysis workflows with COSMIC data

Helper Functions

The download script includes helper functions for common operations:

Get Common File Paths

python
from scripts.download_cosmic import get_common_file_path

# Get path for mutations file
path = get_common_file_path('mutations', genome_assembly='GRCh38')
# Returns: 'grch38/cosmic/v104/Cosmic_GenomeScreensMutant_Tsv_v104_GRCh38.tar'

# Get path for gene census, pinned to an older release
path = get_common_file_path('gene_census', version='v103')
# Returns: 'grch38/cosmic/v103/Cosmic_CancerGeneCensus_Tsv_v103_GRCh38.tar'

The accepted data_type shortcuts are the ones in the Available Data Types table above (signatures returns None — use the signatures download site).

Troubleshooting

Authentication Errors

Verify email and password are correct
Ensure account is registered at cancer.sanger.ac.uk/cosmic
Check if commercial license is required for your use case

File Not Found / HTTP 400

Verify the archive path against the download page (release, product name, assembly)
Check that the requested release exists (v101–v104 are listed as of 2026-09)
Legacy names (CosmicMutantExport.tsv.gz, cancer_gene_census.csv) and GRCh38/cosmic/latest/... paths from older tutorials are not in the current service
Confirm genome assembly (GRCh37 vs GRCh38) is correct

Large File Downloads

COSMIC files can be several GB in size
Ensure sufficient disk space
Download may take several minutes depending on connection
The script shows download progress for large files

Commercial Use

Commercial R&D, commercial products/services, and patient services or clinical reporting require a COSMIC commercial licence: https://www.cosmickb.org/licensing
Academic (not-for-profit) access is free but requires registration

Integration with Other Tools

COSMIC data integrates well with:

Variant annotation: VEP, ANNOVAR, SnpEff
Signature analysis: SigProfiler, deconstructSigs, MuSiCa
Cancer genomics: cBioPortal, OncoKB, CIViC
Bioinformatics: Bioconductor, TCGA analysis tools
Data science: pandas, scikit-learn, PyTorch

Additional Resources

COSMIC Website: https://cancer.sanger.ac.uk/cosmic
Documentation: https://cancer.sanger.ac.uk/cosmic/help
Release Notes: https://cancer.sanger.ac.uk/cosmic/release_notes
Download page (products, checksums, scripted-download help): https://cancer.sanger.ac.uk/cosmic/download/cosmic
Mutational signatures: https://cancer.sanger.ac.uk/signatures/downloads/
Contact: cosmic@sanger.ac.uk

Citation

When using COSMIC data, cite the current database paper: Sondka Z, Dhir NB, Carvalho-Silva D, et al. COSMIC: a curated database of somatic variants and clinical data for cancer. Nucleic Acids Research. 2024;52(D1):D1210-D1217. doi:10.1093/nar/gkad986

Publisher	AlterLab-IEU
Repository	`AlterLab-Academic-Skills`
Skill name	`alterlab-cosmic`
Stars	84
Forks	16
Bundled files	3
License	MIT
Links	Skill source Repository Homepage

Alterlab Cosmic

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

COSMIC Database

Overview

When to Use This Skill

Does NOT Trigger

Prerequisites

Account Registration

Python Requirements

Quick Start

1. Basic File Download

2. Command-Line Usage

3. Working with Downloaded Data

Available Data Types

Working with COSMIC Data

Genome Assemblies

Versioning

File Formats

Common Analysis Patterns

Data Reference

Helper Functions

Get Common File Paths

Troubleshooting

Authentication Errors

File Not Found / HTTP 400

Large File Downloads

Commercial Use

Integration with Other Tools

Additional Resources

Citation

Bundled files

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

COSMIC Database

Overview

When to Use This Skill

Does NOT Trigger

Prerequisites

Account Registration

Python Requirements

Quick Start

1. Basic File Download

2. Command-Line Usage

3. Working with Downloaded Data

Available Data Types

Working with COSMIC Data

Genome Assemblies

Versioning

File Formats

Common Analysis Patterns

Data Reference

Helper Functions

Get Common File Paths

Troubleshooting

Authentication Errors

File Not Found / HTTP 400

Large File Downloads

Commercial Use

Integration with Other Tools

Additional Resources

Citation

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now