Inbreed Simulation

A C++ simulator that shows the genetic effects of inbreeding. Cousin marriage is extremely common in India, and most people have no idea what it does to their family's gene pool over generations. I built this to show exactly that — with code, data, and graphs, not just words.

Three groups run in parallel threads, each with a different mating strategy for performance

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Biology Behind It

Every person carries two copies of each gene — one from mom, one from dad. There are two kinds of alleles in this simulation: A (healthy, dominant) and a (damaged, recessive).

A single healthy copy is enough. If you have Aa, the A masks the damage and you're fine. The problem is aa — both copies damaged, nothing to mask it. That's when the disease or defect actually shows up.

When cousins reproduce, they share a large chunk of their DNA by descent. So the chance of a child inheriting the same damaged a from both sides goes up significantly. Do this for multiple generations, and the damaged alleles stop being hidden — they get fixed permanently across the entire family line. Once fixed, they don't go away. Every child born after that point carries the cost.

Outbreeding works the opposite way. When parents come from unrelated families, the chances of both carrying the same damaged allele are low. The healthy copy from one parent cancels out the damage from the other.

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GROUPS

INBRED — parents are always drawn from a small family pool of 10, mimicking generational cousin marriage

OUTBRED — parents come from separate unrelated gene pools

MIXED — alternates between inbred and outbred phases

Each individual has 100 diploid loci. Harmful recessive alleles accumulate over generations. The simulation tracks two things:

Average fitness — how healthy the population is on average

Fixed loci — loci where the entire population has become aa permanently, meaning the working gene is gone forever from the gene pool

Features

• Diploid Genome Modeling: Individuals carry two alleles per locus.
• Mendelian Inheritance: Offspring inherit one random allele from each parent per locus.
• Stochastic Mutation: Configurable mutation rates for transitioning dominant alleles (A) to recessive (a).
• Fitness Function: Calculates survival probability based on the count of homozygous recessive (aa) loci using $P(\text{survival}) = (1 - \delta)^n$.

Logic Overview

The simulation utilizes a standard Wright-Fisher approach (under development):

1. Mutation: Alleles flip based on mutation_rate.
2. Recombination: Individual::reproduce simulates independent assortment.
3. Selection: fitness(delta) calculates the biological cost of deleterious mutations.

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Config

All parameters in the simconfig namespace at the top of main.cpp:

Parameter	Default	What it does
POP_SIZE	500	individuals per population
LOCI_COUNT	100	diploid loci per individual
GENERATION	5000	generations to simulate
DELTA	0.3	fitness penalty per aa locus
INBRED_POOL	10	family pool size for inbred mating

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Run

make && python plot.py

Output is written to results.csv

Windows User:
Please modify the output file into .exe in Makefile.
Important Note: The Compiler flags are set compiler that is Native to the Cpu that compiles the program, So The Binary is not a Portable File

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