AlphaGenome Single-Variant Analysis (Claude Skill)

Predict how a non-coding genetic variant changes gene expression, chromatin accessibility, histone marks, splicing, and transcription-factor binding using the AlphaGenome API.

   
Type Claude Skill
Supplier Google DeepMind
Availability Preview — AlphaGenome API is research-preview (signup-gated)
Pricing Free / OSS skill (Apache-2.0 code, CC-BY-4.0 docs); AlphaGenome API free for non-commercial use, key required
Capabilities Read/Write — Claude runs the skill’s Python locally (uv run), calling the AlphaGenome API
Verified degraded · 2026-07-29 — dir still resolves; API remains signup-gated preview
Security cleared · 2026-07-29 — provenance matches google-deepmind, Apache-2.0, key goes only to the first-party AlphaGenome API, no OSV advisories

How to install

The google-deepmind/science-skills collection follows the Agent Skills SKILL.md spec. The repo’s primary npx skills add path targets Gemini/Antigravity; for Claude the followable path is a manual copy of the skill directory.

  • Claude Code / Claude Desktop — clone and copy the skill into your skills directory: 
    git clone https://github.com/google-deepmind/science-skills
cp -r science-skills/skills/alphagenome_single_variant_analysis ~/.claude/skills/
cp -r science-skills/skills/uv ~/.claude/skills/

    (The SKILL.md requires the bundled uv skill for its setup — copy it too.)

  • Set the API key — sign up at deepmind.google.com/science/alphagenome, accept the terms, then: 
    echo "ALPHAGENOME_API_KEY=<your-key>" >> ~/.env

    (replace <your-key> with the key from the AlphaGenome console).

  • Prerequisite — the skill runs all Python via uv run; install uv first if absent: curl -LsSf https://astral.sh/uv/install.sh | sh. The skill installs its own Python deps (pandas, numpy, AlphaGenome client) into an isolated environment on first run.

What it does

Evaluates a single variant (in chr:pos:ref>alt format) against AlphaGenome’s predicted molecular phenotypes: RNA-seq expression, DNASE chromatin accessibility, ChIP histone marks, and transcription-factor binding. Helper scripts:

  • lookup_gene_info.py — gene/transcript lookup via a local GTF (no external call)
  • resolve_ontology_terms.py — map biological terms to UBERON/CL tissue and cell-type ontology IDs
  • visualize_variant_effects.py — reference vs. alternate tracks and splicing visualizations
  • analyze_ism.py — in-silico mutagenesis sequence logos
  • interpret_splicing.py — quantitative splicing-disruption analysis

Primary use cases: non-coding variant effect prediction, regulatory/enhancer/promoter variant interpretation, splicing-disruption analysis.

Notes

Requires an ALPHAGENOME_API_KEY and acceptance of the AlphaGenome terms before first use; the API is a research preview for non-commercial use. The skill resolves genes offline from a local GTF and prohibits direct external gene-lookup API calls. The npx skills add google-deepmind/science-skills/ command documented upstream is oriented at Gemini/Antigravity (it writes to ~/.gemini/config/skills/); for Claude, the manual copy into ~/.claude/skills/ shown above is the equivalent path. AlphaGenome the model itself (weights) is out of scope; this entry is the installable skill wrapper around its hosted API.

Sources

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