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Updated: Jul 16, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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BG2:贝叶斯变量选择在一般化的线性混合模型中,对于非高斯GWAS数据,具有非局部先验

Shuangshuang Xu1, Jacob Williams1, Marco A R Ferreira2

  • 1Department of Statistics, Virginia Tech, Blacksburg, VA, 24061, USA.

BMC bioinformatics
|September 15, 2023
PubMed
概括

这项研究介绍了贝叶斯基因组广泛关联研究 (BG2) 的泛型线性混合模型,这是一种用于识别与非高斯特征相关的遗传变异的新方法. BG2提高了准确性,并处理复杂的数据类型,优于传统的单一标记分析.

关键词:
贝叶斯统计学 贝叶斯统计学在 GLMMM 的情况下,GLMM 是 GLMM.在GWAS中,GWAS就是GWAS.非本地先决的先决性变量选择 变量选择

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