Measurement_noise_genetic_evaluation

A breeding program was simulated to generate comprehensive datasets, including pedigree, true breeding values/fixed effects, and phenotypic records. Phenotypes were constructed from true breeding values and fixed effects with the addition of hierarchical levels of noise to represent measurement error. Using these datasets, pedigree-based BLUP (P-BLUP) analyses were performed, and the resulting output files were used for downstream evaluation and comparison across noise scenarios.

本研究通过模拟育种程序生成了涵盖系谱（pedigree）、真实育种值（true breeding values）、固定效应（fixed effects）与表型记录（phenotypic records）的综合数据集。表型数据由真实育种值与固定效应组合构建，并通过添加层级化噪声以表征测量误差。基于上述数据集开展基于系谱的最佳线性无偏预测（pedigree-based BLUP，简称P-BLUP）分析，所得输出文件被用于不同噪声场景下的下游评估与对比。