Query the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants. Use when a question is about individuals or variants in the 1000 Genomes Project cohort: which individuals carry variants matching specific criteria in a gene or region,

OneKGPd: Individual Level Queries over the 1000 Genomes Project Scope This skill queries the 1000 Genomes Project dataset — the extended high coverage cohort of 3,202 whole genome sequenced individuals, on the GRCh38 assembly. All results are drawn from this cohort, and sample names returned by the skill (for example HG00096 or NA21130 ) identify its participants. Queries resolve against the cohort's per individual genotype data. This supports two complementary classes of question: selecting variants carried within a region (across the whole cohort or within a specified set of individuals), and selecting the individuals who carry variants matching given criteria. Variant selection can be filtered by allele frequency, predicted consequence, clinical significance, AlphaMissense classification, and the other annotation axes listed below. Relatedness between two named individuals is also available. The genotype state in which a variant is carried — heterozygous or homozygous — is a criterion that queries may specify; results are returned as variants or as sample names, not as raw genotypes. When to Use Use this skill when you need to: Find variants carried in a region or set of regions matching some criteria across the whole cohort ( select variants ). Find variants carried in a region or set of regions matching some criteria in specific set of individuals ( select variants in samples ). Find which 1000 Genomes individuals carry variants matching some criteria in a region or set of regions ( select samples ). Count how many individuals carry specific variants ( count samples ). Restrict any variant query to heterozygous only or homozygous only carriage, or query both together (default). Identify which individuals are homozygous reference at a single position ( select samples hom ref ). Determine the relatedness between two named 1000 Genomes individuals — both the degree (twin / 1st / 2nd / 3rd / unrelated) and the KING kinship coefficient ( kinship ). Get dataset totals — sample count, sex split, variant count, assembly ( dataset info ). Variant selection can be specified by KGP allele frequency, gnomAD 4.1 exome and gnomAD 4.1 genome allele frequency, AlphaMissense Score and AlphaMissense Class, ClinVar significance (202502), and VEP annotations (impact, biotype, feature type, variant class, consequences). Do NOT use this skill for: Resolving a gene symbol, rsID, or transcript to coordinates, or fetching reference sequence. Resolve coordinates first (see Coordinate Provenance below), then query this skill with the resolved GRCh38 region. Any cohort other than the 1000 Genomes Project — this skill serves only that dataset. Prerequisites 1. uv : This skill's script is run with uv run , which reads the script's inline dependency metadata and provisions an ephemeral environment. Ensure uv is installed and on PATH (https://docs.astral.sh/uv/). 2. Data use terms : The 1000 Genomes Project data is open; users should be aware of the 1000 Genomes Project / IGSR data use terms (https://www.internationalgenome.org/data). 3. Access constraints : There is no API key, no .env file, and no rate limit token to configure. 4. No credentials required Core Rules Use the Wrappers : ALWAYS execute the provided helper scripts rather than constructing your own client calls or network requests. Use scripts/onekgpd api.py for variant/sample/kinship queries (it handles the connection, streaming, pagination, and JSON serialization), and scripts/onekgpd meta.py for sample/population metadata (offline, see [Sample & population metadata]( sample population metadata offline)). Coordinates MUST be resolved against an authoritative source first — see [Coordinate Provenance]( coordinate provenance mandatory first step). This is mandatory, not advisory. Count before you select : every variant and sample selection has a paired counting command. Call the count command FIRST to size the result set, then select only if the count is manageable. Zygosity defaults to both : selection and counting commands include both heterozygous and homozygous carriage by default. Narrow with het only or hom only when the question is specifically about one state. (You do not need to pass anything to get both.) Output : scripts write full JSON to a file ( output , default under /tmp/ ) and print a concise summary to stdout. Do not read large JSON files into context — use jq or a small disposable uv run python snippet to extract fields. Coordinate Provenance (MANDATORY FIRST STEP) Before any region based query, resolve the gene or feature to GRCh38 coordinates against an authoritative source (for example Ensembl), and query with those resolved coordinates. The assembly must be explicit, and a gene range must be resolved to precise positions before use. This is structural, not advisory: there is no source side guardrail that would catch a misplaced region, so an unverified coordinate produces results for an unintended location with no error. [!CAUTION] The dataset is GRCh38. A GRCh37 coordinate, or any region that does not correctly correspond to the intended feature on GRCh38, will return results for an unintended location without raising an error. Verify the assembly and the resolved coordinates before querying. Command Selection Guide Match the question to the command. Counting commands are cheap and should precede their selection counterpart. Which individuals carry matching variants in a region → count samples then select samples Which variants are carried in a region, cohort wide → count variants then select variants Which variants are carried in a region, within a named set of individuals → count variants in samples then select variants in samples Who is homozygous reference at a single position → count samples hom ref then select samples hom ref Relatedness (degree + coefficient) between two named individuals → kinship Dataset totals (sample count, sex split, variant total, assembly) → dataset info Annotation filters (shared across variant and sample selection/counting) All variant and sample selection commands ( count variants , select variants , their in samples forms, count samples , select samples ) accept the same annotation filters. Different filter fields are combined with AND ; multiple values within one field are combined with OR . Enum values are case insensitive (e.g. missense variant or MISSENSE VARIANT ). These are selection criteria applied on the server. The fields returned on a selected variant are listed under [Variant returning commands]( variant returning commands); a criterion used for filtering is not necessarily echoed back on the returned variant. af lt / af gt : 1000 Genomes dataset allele frequency bounds gnomad exomes af lt / gnomad exomes af gt : gnomAD v4.1 exome AF bounds gnomad genomes af lt / gnomad genomes af gt : gnomAD v4.1 genome AF bounds clin significance : ClinVar significance terms, CSV (e.g. PATHOGENIC,LIKELY PATHOGENIC ) consequence : Sequence Ontology consequence terms, CSV (e.g. MISSENSE VARIANT,STOP GAINED ) impact : VEP impact, CSV ( HIGH,MODERATE,LOW,MODIFIER ) variant type , feature type , bio type : SO variant class / VEP feature / VEP biotype, CSV alpha missense class : AM LIKELY BENIGN,AM LIKELY PATHOGENIC,AM AMBIGUOUS (CSV) alpha missense score lt / alpha missense score gt : AlphaMissense score bounds biallelic only / multiallelic only exclude males / exclude females min len bp / max len bp : alternate allele length bounds (bp) [!NOTE] alpha missense class and alpha missense score are mutually exclusive (the engine ignores the class when a score bound is set). biallelic only and multiallelic only are mutually exclusive. exclude males and exclude females are mutually exclusive. Setting a gt bound greater than or equal to its matching lt bound defines an empty range and will return nothing. [!NOTE] Allele frequency fields use 0.0 to mean "not present in that source." So gnomad exomes af gt 0 selects variants that are in gnomAD exomes; a returned gnomad exomes af of 0.0 means the variant is absent from gnomAD exomes. The same convention for gnomAD genomes AF. Conversely, gnomad exomes af lt / gnomad genomes af lt bounds include unannotated variants: "AF < X in gnomAD" includes variants with gnomAD AF = 0, i.e. unannotated; pair it with gnomad af gt 0 to require presence in gnomAD. [!NOTE] am score of 0.0 means not scored or not annotated by AlphaMissense it does not mean benign . A real AlphaMissense score is always greater than 0. Quick Start Commands Each command writes full JSON to a file ( output PATH , default a temp file) and prints a concise stdout summary. All region/sample commands share: the region input ( chrom / start / end with optional ref / alt , or one or more repeated region CHR:START END ), the zygosity flags ( het only / hom only , default both), and the annotation filters above. The full per flag tables live in [references/onekgpd commands.md](references/onekgpd commands.md). Variant returning commands select return matching variants; count return an integer count. count variants — count variants in a region, cohort wide. select variants — select variants in a region, cohort wide. Use limit N (hard cap, default 200) or page size N (retrieve the full set in pages); the two are mutually exclusive. The summary flags truncated when the cap is reached. count variants in samples — as count variants , restricted to samples NAME1,NAME2,... (required). select variants in samples — as select variants , restricted to samples NAME1,NAME2,... (required). Each returned variant carries these 22 keys: chr , start , end , ref , alt , af , ac , an , hom samples , het samples , mis samples , hom samples fx , het samples fx , mis samples fx , hom samples mxy , het samples mxy , mis samples mxy , gnomad exomes af , gnomad genomes af , am score , amino acids , biallelic . ClinVar significance and VEP consequence are filter criteria only and are not returned. Full schema: [references/onekgpd commands.md](references/onekgpd commands.md). Sample returning commands count samples — count individuals carrying a matching variant in a region. select samples — list the names of individuals carrying a matching variant. Supports skip N and limit N . Returns names only; to see which variants qualified an individual, feed the names into select variants in samples . Homozygous reference commands Single position via chrom + position (not a region). count samples hom ref — count individuals with a 0/0 call at the position. The count is a sentinel: 1 = no variant exists at that position at all; 0 = a variant exists but no individual is homozygous reference; 0 = the number of homozygous reference individuals. The summary states which case. select samples hom ref — list the individuals with a 0/0 call at the position. Relatedness command kinship sample1 NAME sample2 NAME — relatedness between two named individuals: the degree ( TWINS MONOZYGOTIC / FIRST DEGREE / SECOND DEGREE / THIRD DEGREE / UNRELATED ) and the KING kinship coefficient ( phi bwf ). Dataset metadata command dataset info — dataset totals: samples total (3,202), female/male split, variants total , assembly (GRCh38), and the cohort breakdown. No region required; doubles