Gnomad Database
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add google-deepmind/science-skills --skill gnomad-databaseCompatible with
Supported agents
name: "gnomad-database"
description: "Query the Genome Aggregation Database (gnomAD). Use when determining the rarity or allele frequency of specific genetic variants, retrieving gene constraint metrics (pLI, LOEUF) to assess loss-of-func..."
| name | gnomad-database |
| description | > Query the Genome Aggregation Database (gnomAD). Use when determining the rarity or allele frequency of specific genetic variants, retrieving gene constraint metrics (pLI, LOEUF) to assess loss-of-function intolerance, finding variants in a genomic region or gene, or querying structural variants. Don't use for analyzing individual patient genomes, tracking somatic mutations in cancer (use COSMIC), or requesting raw sequencing reads (use ENA). |
uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.All scripts are located in the scripts/ subdirectory of this skill's
installation directory. When running them, use the full absolute path to the
script (e.g. /path/to/gnomad_database/scripts/get_variant_frequency.py).
1. Variant Frequency. Retrieves global and ancestry-specific allele
frequencies, homozygote counts, and Grpmax Filtering AF (faf95/faf99) for
exome, genome, and total (exome+genome combined) data. The filtering allele
frequency (FAF) is the maximum credible genetic ancestry group AF (lower bound
of the 95% or 99% CI). Variant ID format must be chrom-pos-ref-alt (e.g.,
1-55516888-G-GA). Alternately, you may provide an rsID.
# By variant ID:
uv run scripts/get_variant_frequency.py --variant_id {variant_id} [--dataset {dataset}] --output variant_frequency.json
# By rsID (e.g., rs1800562):
uv run scripts/get_variant_frequency.py --rsid {rsid} [--dataset {dataset}] --output variant_frequency.json
2. Gene Constraint. Retrieves constraint metrics for a gene. The response
will explicitly contain pli, and the LOEUF score is represented by
oe_lof_upper.
uv run scripts/get_gene_constraint.py --gene {gene_symbol} --output {gene_symbol}_constraint.json
3. Region/Gene Variant Search. Finds all variants in a region or gene.
# By region:
uv run scripts/search_variants.py --chrom {chrom} --start {start} --end {end} --output region_variants.json
# By gene:
uv run scripts/search_variants.py --gene {gene_symbol} --consequence {pLoF|missense} --output {gene_symbol}_variants.json
Further documentation on the data: https://gnomad.broadinstitute.org/data#api More general database documentation: https://gnomad.broadinstitute.org/help
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongnomad-databaseExecute the skills CLI command in your project's root directory to begin installation:
epx add google-deepmind/science-skills --skill gnomad-databaseFetches gnomad-database from google-deepmind/science-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/gnomad-database
Restart Cursor to activate gnomad-database. Access via /gnomad-databasein your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
literature-search-arxiv
google-deepmind/science-skills · Science · same repo
ucsc-conservation-and-tfbs
google-deepmind/science-skills · Science · same repo
pubchem-database
google-deepmind/science-skills · Science · same repo
optimize-for-gpu
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
statistical-analysis
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
pptx-posters
K-Dense-AI/scientific-agent-skills · Science · 2 shared tags
gnomad-database has been reliable in day-to-day use. Documentation quality is above average for community skills.
gnomad-database reduced setup friction for our internal harness; good balance of opinion and flexibility.
gnomad-database fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
gnomad-database fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added gnomad-database from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
gnomad-database reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added gnomad-database from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
gnomad-database is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
gnomad-database has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added gnomad-database from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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