The genome-wide association studies (GWASs) are essential to determine the genetic bases of either ecological or economic phenotypic variation across individuals within populations of the model and nonmodel organisms. For this research question, the GWAS replication testing different parameters and models to validate the results' reproducibility is common. However, straightforward methodologies that manage both replication and tetraploid data are still missing. To solve this problem, we designed the MultiGWAS, a tool that does GWAS for diploid and tetraploid organisms by executing in parallel four software packages, two designed for polyploid data (GWASpoly and SHEsis) and two designed for diploid data (GAPIT and TASSEL). MultiGWAS has several advantages. It runs either in the command line or in a graphical interface; it manages different genotype formats, including VCF. Moreover, it allows control for population structure, relatedness, and several quality control checks on genotype data. Besides, MultiGWAS can test for additive and dominant gene action models, and, through a proprietary scoring function, select the best model to report its associations. Finally, it generates several reports that facilitate identifying false associations from both the significant and the best-ranked association Single Nucleotide Polymorphisms (SNPs) among the four software packages. We tested MultiGWAS with public tetraploid potato data for tuber shape and several simulated data under both additive and dominant models. These tests demonstrated that MultiGWAS is better at detecting reliable associations than using each of the four software packages individually. Moreover, the parallel analysis of polyploid and diploid software that only offers MultiGWAS demonstrates its utility in understanding the best genetic model behind the SNP association in tetraploid organisms. Therefore, MultiGWAS probed to be an excellent alternative for wrapping GWAS replication in diploid and tetraploid organisms in a single analysis environment.

中文翻译：

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MultiGWAS：四倍体生物全基因组关联研究的综合工具

全基因组关联研究 (GWAS) 对于确定模型和非模型生物种群内个体之间生态或经济表型变异的遗传基础至关重要。对于这个研究问题，GWAS 复制测试不同的参数和模型以验证结果的可重复性很常见。然而，管理复制和四倍体数据的直接方法仍然缺失。为了解决这个问题，我们设计了 MultiGWAS，这是一种通过并行执行四个软件包对二倍体和四倍体生物进行 GWAS 的工具，两个专为多倍体数据设计（GWASpoly 和 SHEsis），两个专为二倍体数据设计（GAPIT 和 TASSEL）。MultiGWAS 有几个优点。它在命令行或图形界面中运行；它管理不同的基因型格式，包括 VCF。此外，它允许控制人口结构、相关性和对基因型数据的几个质量控制检查。此外，MultiGWAS 可以测试加性和显性基因作用模型，并通过专有评分功能选择最佳模型来报告其关联。最后，它生成几个报告，有助于从四个软件包中的重要和排名最高的关联单核苷酸多态性 (SNP) 中识别错误关联。我们使用公共四倍体马铃薯块茎形状数据和加性模型和优势模型下的几个模拟数据测试了 MultiGWAS。这些测试表明 MultiGWAS 在检测可靠关联方面比单独使用四个软件包中的每一个都更好。而且，仅提供 MultiGWAS 的多倍体和二倍体软件的并行分析证明了其在理解四倍体生物中 SNP 关联背后的最佳遗传模型方面的实用性。因此，MultiGWAS 被认为是在单一分析环境中将 GWAS 复制包装在二倍体和四倍体生物中的绝佳替代方案。