# Cancer Genomics Analysis

Computational cancer genomics workflows.

- Repository: https://github.com/synthetic-sciences/openscience (4321 stars)
- Category: Data and ML
- License: MIT license
- Last updated: 2026-10-30
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add synthetic-sciences/openscience --skill cancer-genomics-analysis -g -a claude-code -y`
Codex: `npx skills add synthetic-sciences/openscience --skill cancer-genomics-analysis -g -a codex -y`
Cursor: `npx skills add synthetic-sciences/openscience --skill cancer-genomics-analysis -g -a cursor -y`
Gemini CLI: `npx skills add synthetic-sciences/openscience --skill cancer-genomics-analysis -g -a gemini-cli -y`

## Description

Computational cancer genomics workflows. Somatic mutation detection and annotation, structural variation characterization, copy number analysis, tumor purity/ploidy estimation, NMF metagene extraction, and DNA damage response network analysis. For cancer mutation databases use cosmic-database; for variant clinical significance use clinvar-database.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Cancer Genomics Analysis: Computational Workflows

## Overview

Cancer Genomics Analysis provides computational pipelines for processing and interpreting cancer genomics data. This skill covers somatic mutation detection and annotation (GATK Mutect2 integration), structural variation characterization, copy number analysis (CNVkit workflows), tumor purity and ploidy estimation, NMF-based metagene extraction from expression data, DNA damage response network analysis, and tumor mutational burden calculation. All workflows produce quantitative outputs suitable for clinical interpretation and publication.

## When to Use This Skill

- Processing somatic variant calls from tumor-normal paired sequencing
- Annotating VCF files with gene names, functional impact, and clinical significance
- Detecting and classifying structural variants (deletions, duplications, inversions, translocations)
- Running copy number analysis pipelines (coverage, segmentation, calling)
- Estimating tumor purity and ploidy from sequencing data
- Extracting gene expression signatures via NMF (metagene programs)
- Analyzing DNA damage response pathway disruption in tumors
- Calculating tumor mutational burden for immunotherapy biomarker assessment

**Related Skills:** For cancer mutation databases use `cosmic-database`. For variant clinical significance use `clinvar-database`. For gene annotations use `ensembl-database`. For pathway enrichment use `kegg-database` or `reactome-database`.

## Installation

```bash
uv pip install pyvcf3 cyvcf2 pysam scikit-learn networkx gseapy pandas numpy matplotlib
```

For command-line tools (optional):
```bash
# GATK, SnpEff, CNVkit are installed separately
# conda install -c bioconda gatk4 snpeff cnvkit
```

## Quick Start

```python
import cyvcf2
import pandas as pd

The rest: https://github.com/synthetic-sciences/openscience/blob/HEAD/backend/cli/skills/biology/cancer-genomics-analysis/SKILL.md