Query 1000 Genomes Project participant and variant data with GRCh38 region counting.
npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill onekgpd
Please help me install this Agent Skill. Skill: onekgpd Source: https://github.com/jasrajtulsi/GRAD-SCOPE/tree/main/.claude/skills/onekgpd Command: npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill onekgpd
It removes the friction of manually exploring 1000 Genomes Project data by turning cohort queries, variant lookups, and sample selection into repeatable, precise workflows.
Ask the skill to query the 1000 Genomes Project for a GRCh38 region or sample set you already resolved and specify whether you want counts, matching individuals, or the underlying variants.
High-intent search queries and answers about installing and using this skill.
Query 1000 Genomes Project participant data by specifying validated GRCh38 coordinates and sample sets to retrieve matching individuals, variant counts, or underlying variants. The workflow requires zygosity controls, annotation filters, and pagination for precise cohort analysis.
Identify homozygous-reference calls and perform kinship checks between 1000 Genomes samples directly. The skill supports individual-level analysis to determine which samples carry matching variants and how closely two participants are related using bundled pedigree data.
Count variants across GRCh38 regions by defining the genomic interval and restricting the query to named samples or specific populations. You can resolve a gene to coordinates, find variants in that interval, and narrow results to a selected population group.
Querying 1000 Genomes population metadata does not require a network connection. The skill bundles sample pedigrees, populations, and superpopulations offline, allowing you to look up cohort metadata and perform reproducible analysis without external network access.
Limitations include the requirement for validated GRCh38 coordinates, strict zygosity controls, annotation filters, and pagination. Reproducible cohort analysis depends on providing precise inputs and correctly managing the bundled pedigree data to avoid inaccurate sample selection.
google-deepmindResolve genetic variants between rsIDs, VCF coordinates, and HGVS via dbSNP.
jaechang-hitsRun PLINK2 GWAS association testing with quality control and principal component analysis.
TianGzlabParse, classify, and filter VCF variants with QUAL and DP metrics.
bigbioIngest 1000 Genomes VCFs and sample metadata into Hail MatrixTables.
