BACKGROUND Genomic prediction (GP) is a method whereby DNA polymorphism information is used to predict breeding values for complex traits. Although GP can significantly enhance predictive accuracy, it can be expensive and difficult to implement. To help design optimum breeding programs and experiments, including genome-wide association studies and genomic selection experiments, we have developed SeqBreed, a generic and flexible forward simulator programmed in python3. RESULTS SeqBreed accommodates sex and mitochondrion chromosomes as well as autopolyploidy. It can simulate any number of complex phenotypes that are determined by any number of causal loci. SeqBreed implements several GP methods, including genomic best linear unbiased prediction (GBLUP), single-step GBLUP, pedigree-based BLUP, and mass selection. We illustrate its functionality with Drosophila genome reference panel (DGRP) sequence data and with tetraploid potato genotype data. CONCLUSIONS SeqBreed is a flexible and easy to use tool that can be used to optimize GP or genome-wide association studies. It incorporates some of the most popular GP methods and includes several visualization tools. Code is open and can be freely modified. Software, documentation, and examples are available at https://github.com/miguelperezenciso/SeqBreed.

中文翻译：

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SeqBreed：一个在复杂情况下评估基因组预测的python工具。

背景技术基因组预测（GP）是一种利用DNA多态性信息来预测复杂性状育种值的方法。尽管GP可以显着提高预测准确性，但它可能昂贵且难以实施。为了帮助设计最佳的育种程序和实验，包括全基因组关联研究和基因组选择实验，我们开发了SeqBreed，这是一种用python3编程的通用且灵活的正向模拟器。结果SeqBreed可容纳性和线粒体染色体以及自身多倍体。它可以模拟由任意数量的因果基因座决定的任意数量的复杂表型。SeqBreed实现了几种GP方法，包括基因组最佳线性无偏预测（GBLUP），单步GBLUP，基于谱系的BLUP和质量选择。我们用果蝇基因组参考面板（DGRP）序列数据和四倍体马铃薯基因型数据说明其功能。结论SeqBreed是一种灵活且易于使用的工具，可用于优化GP或全基因组关联研究。它包含了一些最流行的GP方法，并包括了几种可视化工具。代码是开放的，可以自由修改。可从https://github.com/miguelperezenciso/SeqBreed获得软件，文档和示例。