alphafold_database_fet…
Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides…
Constructs deep-links and URLs for the AlphaGenome Atlas website. Supports generating single-variant exploration links (1-based chr:pos:ref>alt), genomic locus views (1-based closed chr:start-end), candidate summary tables, and AlphaGenome reference vs. alternate predictions.
$ npx -y skills add google-deepmind/science-skills --skill alphagenome_atlas_website_links --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/alphagenome_atlas_website_linksContext preview
The summary Claude sees to decide when to auto-load this skill.
Constructs deep-links and URLs for the AlphaGenome Atlas website. Supports generating single-variant exploration links (1-based chr:pos:ref>alt), genomic locus views (1-based closed chr:start-end), candidate summary tables, and AlphaGenome reference vs. alternate predictions.
name: alphagenome-atlas-website-links description: >- Constructs deep-links and URLs for the AlphaGenome Atlas website. Supports generating single-variant exploration links (1-based chr:pos:ref>alt), genomic locus views (1-based closed chr:start-end), candidate summary tables, and AlphaGenome reference vs. alternate predictions. Use whenever visualizing, exploring, charting, or linking genetic variants and genomic loci on the AlphaGenome Atlas, or when asked to inspect, view, or link predictions for a genomic variant.
Construct and validate deep-links for the AlphaGenome Atlas web application (`https://deepmind.google.com/science/alphagenome/atlas`).
Base URL: `https://deepmind.google.com/science/alphagenome/atlas`
> [!IMPORTANT] **Mandatory Atlas Deep-Linking with Variant Scores**: Whenever > presenting, discussing, or scoring genetic variants, you **MUST always provide > clickable deep-links to the > [AlphaGenome Atlas](https://deepmind.google.com/science/alphagenome/atlas)**. > Use `scripts/alphagenome_atlas_links.py` to automate link and table > generation.
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# 1. Single Variant Exploration Link: uv run scripts/alphagenome_atlas_links.py variant "chr9:128225994:G>A" \ --biosample K562 \ --modalities RNA_SEQ,DNASE,CHIP_TF # 2. Genomic Locus / Interval Link: uv run scripts/alphagenome_atlas_links.py locus "chr11:5288500-5290500" \ --biosample K562 \ --modalities RNA_SEQ,DNASE,CHIP_TF # 3. Format Candidate Variant Records Table (with embedded clickable links): uv run scripts/alphagenome_atlas_links.py table --input top_variants.json --biosample K562 # 4. Construct Ref vs. Alt Track Predictions Link (/atlas/track-predictions): uv run scripts/alphagenome_atlas_links.py track-predictions \ --variant "chr15:42387805:C>G" \ --gene CAPN3 \ --biosample "Muscle_Skeletal"
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closed intervals (`chr11:5288500-5290500`), gene symbols (`BRCA1`), Ensembl IDs (`ENSG00000012048`), or 1-based variants (`chr7:27170000:A>G`).
genes/variants and `locus` for coordinate intervals. Use `variant` for variant queries. (Allowed: `locus`, `entity`, `variant`, `motifs`).
closed `chr:start-end` format (e.g. `chr11:5289310-5289690`). Required for automatic motif rendering.
`KEY:VALUE` format (e.g. `BIOSAMPLE_NAME:K562,SCORER_MODALITY:RNA-seq,ASSAY_TRANSCRIPTOR_FACTOR:GATA1`). Controls visible heatmap rows.
toggle (`avi`), section heatmaps, and pinned tracks list (e.g. `avi,section:RNA_SEQ,section:DNASE,pinned:<TrackKey>`).
for the `/atlas/track-predictions` page comparison (e.g. `<ScoreId1>,<ScoreId2>`).
predictions view (`RNA_SEQ`, `SPLICE_JUNCTIONS`, `SPLICE_SITE_USAGE`, `DNASE`).
score predictions (`ScoreId:CustomTitle`).
predictions chart card (e.g. `Predicted Gene Expression`).
> [!IMPORTANT] **Variant Query Format**: Variants in `q` must strictly use > `chr:pos_1_based:ref>alt` format (e.g. `chr7:27170000:A>G` or URL-encoded > `chr7:27170000:A%3EG`, where the position is 1-based). **Do not use** > colon-separated alleles (`A:G`) or dbSNP rsIDs (rsIDs are unsupported).
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Filters in `f` map to three primary evaluation groups:
**AND** logic.
`ASSAY_HISTONE_MARK`)**: Evaluated with **OR** logic.
`RNA-seq` and `DNase` tracks have no transcription factor code (`transcriptionFactorCode === ""`). If `f` contains *only* `ASSAY_TRANSCRIPTOR_FACTOR` filters under the Assay group, `RNA-seq` and `DNase` tracks fail the Assay evaluation and are hidden from the heatmap.
To display `RNA-seq` and `DNase` tracks alongside specific ChIP-seq transcription factors, **explicitly include `SCORER_MODALITY:RNA-seq` and `SCORER_MODALITY:DNase`** in `f` (handled automatically by `scripts/alphagenome_atlas_links.py`):
f=BIOSAMPLE_NAME:<CellLine>,SCORER_MODALITY:RNA-seq,SCORER_MODALITY:DNase,ASSAY_TRANSCRIPTOR_FACTOR:<TF1>,ASSAY_TRANSCRIPTOR_FACTOR:<TF2>
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the top-level AlphaGenome Variant Impact score track for the interval or variant.
unpinned heatmaps across all matching tracks for that modality (e.g. `section:RNA_SEQ`, `section:DNASE`, `section:CHIP_TF`, `section:ATAC`, `section:CAGE`).
> [!NOTE] **Track-Specific Motif Guideline**: Pi
A collection of agent skills for scientific research tasks, spanning genomics, structural biology, cheminformatics, literature search, and more.
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