### Gnomad Database
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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..."
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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:
Fetches 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:
Restart Cursor to activate gnomad-database. Access via /gnomad-database in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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| 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
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
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.
google-deepmind/science-skills
google-deepmind/science-skills
google-deepmind/science-skills
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
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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