Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
Department of Mathematics, Egerton University, Egerton 536-20115, Kenya.
Genomics Proteomics Bioinformatics. 2020 Aug;18(4):481-487. doi: 10.1016/j.gpb.2020.06.006. Epub 2020 Dec 18.
Previous studies have reported that some important loci are missed in single-locus genome-wide association studies (GWAS), especially because of the large phenotypic error in field experiments. To solve this issue, multi-locus GWAS methods have been recommended. However, only a few software packages for multi-locus GWAS are available. Therefore, we developed an R software named mrMLM v4.0.2. This software integrates mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, and ISIS EM-BLASSO methods developed by our lab. There are four components in mrMLM v4.0.2, including dataset input, parameter setting, software running, and result output. The fread function in data.table is used to quickly read datasets, especially big datasets, and the doParallel package is used to conduct parallel computation using multiple CPUs. In addition, the graphical user interface software mrMLM.GUI v4.0.2, built upon Shiny, is also available. To confirm the correctness of the aforementioned programs, all the methods in mrMLM v4.0.2 and three widely-used methods were used to analyze real and simulated datasets. The results confirm the superior performance of mrMLM v4.0.2 to other methods currently available. False positive rates are effectively controlled, albeit with a less stringent significance threshold. mrMLM v4.0.2 is publicly available at BioCode (https://bigd.big.ac.cn/biocode/tools/BT007077) or R (https://cran.r-project.org/web/packages/mrMLM.GUI/index.html) as an open-source software.
先前的研究报告称，单基因座全基因组关联研究（GWAS）可能会遗漏一些重要的基因座，尤其是由于田间试验中存在较大的表型误差。为了解决这个问题，推荐使用多基因座 GWAS 方法。然而，目前可用的多基因座 GWAS 软件包很少。因此，我们开发了一个名为 mrMLM v4.0.2 的 R 软件。该软件集成了 mrMLM、FASTmrMLM、FASTmrEMMA、pLARmEB、pKWmEB 和我们实验室开发的 ISIS EM-BLASSO 方法。mrMLM v4.0.2 有四个组件，包括数据集输入、参数设置、软件运行和结果输出。data.table 中的 fread 函数用于快速读取数据集，尤其是大型数据集，并且使用 doParallel 包使用多个 CPU 进行并行计算。此外，还提供了基于 Shiny 的图形用户界面软件 mrMLM.GUI v4.0.2。为了确认上述程序的正确性，使用了 mrMLM v4.0.2 中的所有方法和三种广泛使用的方法来分析真实和模拟数据集。结果证实了 mrMLM v4.0.2 相对于当前可用的其他方法的优越性能。尽管使用了更严格的显著性阈值，但有效控制了假阳性率。mrMLM v4.0.2 可在 BioCode（https://bigd.big.ac.cn/biocode/tools/BT007077）或 R（https://cran.r-project.org/web/packages/mrMLM.GUI/index.html）上作为开源软件公开获取。
