College of Life Science and College of Animal Scientific and Technology, Northeast Agricultural University, Harbin, 150030, China.
College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, 163319, China.
Theor Appl Genet. 2022 Jun;135(6):2147-2155. doi: 10.1007/s00122-022-04103-1. Epub 2022 May 10.
In extension of Single-RunKing to analyze multiple correlated traits, mvRunKing not only enlarged number of the analyzed phenotypes with canonical transformation, but also improved statistical power to detect pleiotropic QTNs through joint association analysis. Based on genomic variance-covariance matrices, we simplified multivariate mixed model association analysis to multiple univariate ones by using canonical transformation, and then individually implemented univariate association tests in the Single-RunKing. which enlarged number of the analyzed phenotypes. With canonical transformation back to the original scale, the association results would be biologically interpretable. Especially, we rapidly estimated genomic variance-covariance matrices with multivariate GEMMA and optimized separately the polygenic variances (or heritabilities) for only the markers that had large effects or higher significance levels in univariate mixed models, greatly improving computing efficiency for multiple univariate association tests. Beyond one test at once, joint association analysis for quantitative trait nucleotide (QTN) candidates can significantly increase statistical powers to detect QTNs. A user-friendly mvRunKing software was developed to efficiently implement multivariate mixed model association analyses.
为了将 Single-RunKing 扩展到分析多个相关性状，mvRunKing 不仅通过正则变换扩大了分析表型的数量，而且通过联合关联分析提高了检测多效性 QTN 的统计能力。基于基因组方差协方差矩阵，我们通过正则变换将多变量混合模型关联分析简化为多个单变量分析，然后在 Single-RunKing 中分别执行单变量关联测试，从而扩大了分析表型的数量。通过正则变换回到原始尺度，关联结果将具有生物学可解释性。特别是，我们使用多元 GEMMA 快速估计基因组方差协方差矩阵，并分别优化只有在单变量混合模型中具有较大效应或更高显著性水平的标记的多基因方差（或遗传力），极大地提高了多变量关联测试的计算效率。除了一次一次地进行单一测试外，对数量性状核苷酸 (QTN) 候选物的联合关联分析可以显著提高检测 QTN 的统计能力。开发了一个用户友好的 mvRunKing 软件，以有效地实现多变量混合模型关联分析。
