emmax-prep-skill

分类: 数据与AI | 上传者: YYsama11 | 下载: 0 | 版本: v1.0（最新）

Use when you need to transform filtered genotype data plus phenotype and covariate tables into EMMAX-ready inputs including TPED/TFAM, kinship, PCA covariates, and sample-intersected trait matrices.

更新日志: Source: GitHub https://github.com/YYsama11/BreedingSkills

目录结构

当前层级: skills/emmax-prep-skill/

📁 assets/
- 📄 genotype_kinship_prep.env.template 203 B
📁 references/
- 📄 input_contract.md 698 B
- 📄 workflow.md 716 B
📁 scripts/
- 📄 run_genotype_kinship_prep.sh 2.5 KB
📄 SKILL.md 1.4 KB

SKILL.md

---
name: emmax-prep-skill
description: Use when you need to transform filtered genotype data plus phenotype and covariate tables into EMMAX-ready inputs including TPED/TFAM, kinship, PCA covariates, and sample-intersected trait matrices.
---

# emmax-prep-skill

## When to use

- You already have a filtered VCF or PLINK dataset
- You need to reconcile sample intersections, covariates, PCA, and kinship
- The downstream association engine is fixed to `emmax-intel64`

## Quick start

- Prepare genotype and phenotype matrices as described in `references/input_contract.md`
- Copy and edit `assets/genotype_kinship_prep.env.template`
- Use `emmax-intel64` and `emmax-kin-intel64` as the default binary names; do not assume a plain `emmax` executable exists in `PATH`
- Run `bash scripts/run_genotype_kinship_prep.sh --config assets/genotype_kinship_prep.env.template`

## Default workflow

1. Validate genotype, phenotype, and sample identifiers
2. Convert the VCF into EMMAX-compatible `tped/tfam`
3. Build PLINK binaries and compute PCA covariates
4. Generate the kinship matrix
5. Extract trait names and write a trait manifest for batch GWAS

## Primary outputs

- `trait_list.txt`
- `workflow_plan.txt`
- `emmax/`
- `covariates/`
- `intermediate/`

## Read only when needed

- Input matrix rules: `references/input_contract.md`
- `emmax-intel64` preparation details: `references/workflow.md`

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emmax-prep-skill

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SKILL.md

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