Produce offspring genomes from parent pairs via meiotic recombination, mutation, and clinical evaluation
Scanned 9/4/2026
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---
name: recombinator
description: Produce offspring genomes from parent pairs via meiotic recombination, mutation, and clinical evaluation
license: MIT
metadata:
version: 0.1.0
author: Manuel Corpas
tags:
- genomebook
- recombination
- meiosis
- mutation
- offspring
- clinical-genetics
openclaw:
requires:
bins:
- python3
always: false
emoji: 🧪
homepage: https://github.com/ClawBio/ClawBio
os:
- darwin
- linux
trigger_keywords:
- recombinator
- recombination
- offspring
- breed
- meiosis
- genomebook breed
- next generation
---
# 🧪 Recombinator
## Purpose
Produce offspring genomes from selected parent pairs via simulated meiotic
recombination. Models Mendelian segregation, de novo mutation, sex determination,
and clinical evaluation against a disease registry.
## How It Works
1. **Mendelian segregation**: one allele inherited from each parent per locus
(random selection simulating independent assortment).
2. **De novo mutation**: configurable rate per locus (default 0.1%), with hotspot
multipliers for cognitive, immune, and metabolic loci. Mutations are classified
as disease-risk, protective, or neutral.
3. **Sex determination**: 50/50 coin flip (XY or XX).
4. **Trait inference**: reverse-map offspring genotype back to trait scores using
the trait registry, accounting for dominance models.
5. **Clinical evaluation**: check offspring genotype against disease registry for
penetrance, onset probability, and fitness cost.
6. **Health score**: computed from cumulative fitness costs of clinical conditions.
## Input
- Two parent `.genome.json` files (one Male, one Female)
- `GENOMEBOOK/DATA/trait_registry.json`
- `GENOMEBOOK/DATA/disease_registry.json`
## Output
- Offspring `.genome.json` with:
- Inherited loci and alleles
- Mutation log
- Inferred trait scores
- Clinical history
- Health score (0.0 to 1.0)
## CLI Usage
```bash
# Demo: breed Einstein x Anning, produce 3 offspring
python skills/recombinator/recombinator.py --demo
# Breed specific parents
python skills/recombinator/recombinator.py \
--father einstein-g0 --mother anning-g0 --offspring 3
# Custom generation number
python skills/recombinator/recombinator.py \
--father einstein-g0 --mother curie-g0 --offspring 2 --generation 1
```
## Output Format
```
ID: g1-001-a3f2c1
Sex: Female (XX)
Health: 0.9500
Mutations: 1
- COMT_Val158Met: G->A (neutral, from mother)
Conditions: 0
Top traits:
- curiosity: 0.92
- analytical_thinking: 0.88
- persistence: 0.85
```
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