alphagenome

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Look up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and quantile scores for RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map tracks), score variants or scan windows on demand with the AlphaGenome model for human and mouse (variant scoring, in silico mutagenesis, REF-versus-ALT track prediction), and build Atlas website deep links. Use when the user mentions AlphaGenome, AlphaGenome Atlas, AVI or AlphaGenome Variant Impact, DeepMind variant effect prediction, or wants to prioritise or mechanistically interpret non-coding, regulatory, splicing, enhancer, promoter, or chromatin-accessibility effects of SNVs from a VCF, credible set, or region. Research use only; not a clinical tool.

AI & Automation 46,700 stars 4221 forks Updated 5 days ago MIT

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Skill Content

# AlphaGenome and the AlphaGenome Atlas AlphaGenome is DeepMind's sequence-to-function model: 1 Mb of DNA in, base-pair predictions for eleven assay types across thousands of human and mouse tracks out. The **AlphaGenome Atlas** (released 2026-09-08) is that model run once over every possible single-nucleotide change in GRCh38, about 9 billion variants, stored with a single ranking number, the **AlphaGenome Variant Impact (AVI)** score, its genome-wide percentile, and an 18-way attribution of what drives it. Both are reached through one `pip install alphagenome` and one API key. > Research and theoretical modelling only. Outputs must not be used to train > other models, and are not for diagnostic procedures or medical decisions. ## When to use which | You have | Use | Why | | --- | --- | --- | | hg38 SNVs (a VCF, a credible set, a region up to ~1 kb) | **Atlas** via `scripts/atlas_query.py` | precomputed, higher quota, includes AVI and attributions | | indels, mouse variants, a non-reference background, a custom scorer or window | **model** via `scripts/score_variants.py` or Python | the Atlas is SNV-only and hg38-only | | a hypothesis to explain (which motif, which tissue, REF vs ALT tracks) | model `predict_variant` + plots, Atlas track scores, portal link | mechanism, not just rank | | GRCh37 coordinates, rsIDs, unnormalised indels | `genomic-coordinates` first, then come back | wrong build or swapped REF gives a plausible wrong answer | | ClinVar assertions, gene-dise...

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Author
K-Dense-AI
Repository
K-Dense-AI/scientific-agent-skills
Created
11 months ago
Last Updated
5 days ago
Language
Python
License
MIT

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