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AlphaGenome Variant Impact Analysis

Look up precomputed AlphaGenome Atlas AVI scores and call the AlphaGenome model on demand to rank and mechanistically interpret non-coding regulatory SNVs.

Data & AnalyticsAdvanced★ 44,742⑂ 4,060AI score 8/10Last updated: Sep 13, 2026

What it does

  • Atlas lookups: pulls precomputed AVI scores (raw value, genome-wide quantile, Phred conversion) plus 18 SHAP feature attributions for any GRCh38 SNV (~9 billion variants) via scripts/atlas_query.py.
  • Track-level mechanism: RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map scores, filterable by tissue/ontology CURIE.
  • On-demand model scoring: for indels, mouse (mm10), custom windows or scorers, use scripts/score_variants.py or the Python SDK — including REF-vs-ALT track prediction and in silico mutagenesis (ISM).
  • Portal deep links: scripts/atlas_link.py builds Atlas website URLs offline, no key needed.
  • Built-in interpretation discipline: rank rather than threshold, always report raw score and quantile with scorer/track/biosample/gene, and avoid the high-quantile-in-a-quiet-region artefact.

Who it's for

  • Genomics researchers prioritising regulatory variants from a VCF or a GWAS/fine-mapping credible set.
  • Functional genomics analysts probing splicing, enhancer, promoter or chromatin-accessibility hypotheses.
  • Bioinformatics engineers wiring the free non-commercial AlphaGenome API into a pipeline.

Example uses

  1. python atlas_query.py avi --input candidates.vcf --min-phred 20 -o avi.tsv — keep only the top 1% and emit a ranked table.
  2. python atlas_query.py scores --variant chr22:36201698:A>C --scorers RNA_SEQ DNASE --ontology UBERON:0001157 — see which colon tracks drive the effect.
  3. For indels or mouse variants: score_variants.py --organism mouse --variant chr7:45000000:A>G to work around the Atlas's SNV-only, hg38-only limits.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/alphagenome/SKILL.md

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Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
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Install in Claude Code

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Install the skill I found on Claude Skill Mart.
Copy the skills/alphagenome folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/alphagenome/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git && mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/alphagenome ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Prerequisites: Python 3.10+ (tested on 3.12/3.13) and Claude Code installed.
  2. Clone the repo: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Copy the skill: mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/alphagenome ~/.claude/skills/
  4. Install the package: pip install "alphagenome>=0.9.0" (or uv pip install alphagenome).
  5. Get an API key: request a free non-commercial key at https://deepmind.google.com/science/alphagenome and set export ALPHAGENOME_API_KEY="..." (never commit it to a file).
  6. Verify: cd ~/.claude/skills/alphagenome/scripts && python atlas_query.py scorers — a printed scorer list confirms key and network access.
  7. Use it: in Claude Code ask something like "rank the variants in this VCF with AlphaGenome AVI" and the skill triggers automatically.
View source on GitHub ↗License: MIT