ancestry

Project genome data onto 1000 Genomes reference panels for ancestry analysis.

475|61|Updated May 28, 2026

Search Tags:#genomics #ancestry #population context #PCA projection #reference panel

Ready to run

npx skills add https://github.com/exon-research/genomi --skill ancestry

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ancestry
Source: https://github.com/exon-research/genomi/tree/main/skills/ancestry
Command: npx skills add https://github.com/exon-research/genomi --skill ancestry

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ancestry-1000g-30x-grch38, ancestry-1000g-30x-grch37, liftover-chains, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides tools for analyzing and projecting ancestry from genome data, offering insights into population context and reference panel similarity.

Core Features & Use Cases

Ancestry Analysis: Use local ancestry reference-panel tools for PCA projection, marker overlap QC, and reference-neighbor context.
Population Context: Estimate population context and similarity using 1000 Genomes reference panels.
Use Case: If a user asks about their ancestry or population origin, this Skill can provide a qualitative assessment based on their genome data.

Quick Start

Analyze the ancestry of your genome using the ancestry skill and provide the genome source file.

Frequently Asked Questions about ancestry

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I analyze ancestry from my genome data?▼

You can estimate ancestry from genome data by applying PCA projection and marker overlap quality control against 1000 Genomes reference panels. This provides a qualitative assessment of your population context and origin.

What is PCA projection for population context in genomics?▼

PCA projection in genomics maps your genome data onto 1000 Genomes reference panels to estimate population context. It identifies reference-neighbor similarity to provide qualitative ancestry insights and population origin estimates.

Do I need specific reference panels to project ancestry from genome data?▼

Yes, ancestry analysis requires access to specific 1000 Genomes reference panels, including ancestry-1000g-30x-grch38 and ancestry-1000g-30x-grch37. These panels provide the baseline population data needed for PCA projection.

Can I use GRCh37 genome data for ancestry analysis?▼

Yes, you can use GRCh37 genome data for ancestry analysis with the ancestry-1000g-30x-grch37 reference panel. The Skill also supports GRCh38 data and includes liftover-chains for coordinate conversion between genome builds.

Why does my ancestry analysis require marker overlap quality control?▼

Marker overlap quality control ensures your genome data aligns correctly with the 1000 Genomes reference panels before PCA projection. Without this step, mismatched genetic markers could skew your ancestry and population context results.

What is the best way to estimate population origin from a genome source file?▼

The best way to estimate population origin is using local ancestry reference-panel tools that perform PCA projection and marker overlap QC. This approach compares your genome against 1000 Genomes data to determine reference-neighbor similarity.