给出完整MATLAB代码，证明基因对在动物遗传过程中所占的比例基本保持不变，基因对有AA、Aa、aa

在MATLAB中，验证基因频率在种群遗传过程中是否稳定，通常涉及到孟德尔遗传定律和哈代-温伯格平衡（Hardy-Weinberg Equilibrium）。假设我们有一个二态等位基因（比如A/a），我们可以模拟随机交配并检查每个基因对（AA, Aa, aa）的频率是否接近理论值。以下是简单的代码示例：

% 定义初始基因频率
p = 0.6;  % 基因A的频率
q = 1 - p;  % 基因a的频率

% 设置世代数和种群大小
generations = 100;  % 遗传过程世代数
population_size = 1000;

% 初始化基因组合数组
genotypes = zeros(generations, population_size, 2);

% 孟德尔随机交配（Hardy-Weinberg平衡）
for gen = 1:generations
    parents = randi([0 1], population_size, 2);  % 父母的基因组合
    offspring = parents + (rand(population_size, 2) < 2 * [p q]).*2 - 1;  % 子代随机继承父母的基因
    
    % 更新基因组合
    genotypes(gen, :, :) = offspring;
end

% 计算每一代的基因对频率
frequencies = sum(genotypes == [1 1], 2)/population_size;  % AA
frequencies_Aa = sum(genotypes == [1 0], 2)/population_size;  % Aa
frequencies_aa = sum(genotypes == [0 0], 2)/population_size;  % aa

% 检查是否接近理论值
expected_frequencies = [p^2, 2*p*q, q^2];  % 根据H-W定律的期望值
deviations = abs(frequencies - expected_frequencies);
mean_deviation = mean(deviations);

% 输出结果
disp(['After ' num2str(generations) ' generations, mean deviation: ' num2str(mean_deviation)])

% 绘制基因频率变化趋势
plot(frequencies(1:end-1, :), '.-');
xlabel('Generation');
ylabel('Gene Pair Frequency');
title('Gene Frequency Over Generations');