Testing for dependence on tree structures
Testing for dependence on tree structures
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DOI：
10.1073/pnas.1912957117
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发表时间：
2020-05-05
影响因子：
11.1
通讯作者：
Holmes, Chris
中科院分区：
文献类型：
--
作者：
Behr, Merle;Ansari, M. Azim;Holmes, Chris
树结构是基因组和生物医学中普遍存在的一种结构，它显示了样本之间的层次关系和潜在结构。许多研究中的一个常见问题是，在每个样本上测量的响应变量与某些给定树表示的潜在基团结构之间是否存在关联。目前，这是在特定的基础上解决的，通常需要用户决定要从树中删除的适当数量的集群，以针对响应变量进行测试。在这里，我们提出了一种具有统计保证的统计方法，该方法以高功率在树层次的所有级别上测试响应变量与固定树结构之间的关联，同时考虑到总的误报错误率。这增强了这些发现的稳健性和可重复性。
Tree structures, showing hierarchical relationships and the latent structures between samples, are ubiquitous in genomic and biomedical sciences. A common question in many studies is whether there is an association between a response variable measured on each sample and the latent group structure represented by some given tree. Currently, this is addressed on an ad hoc basis, usually requiring the user to decide on an appropriate number of clusters to prune out of the tree to be tested against the response variable. Here, we present a statistical method with statistical guarantees that tests for association between the response variable and a fixed tree structure across all levels of the tree hierarchy with high power while accounting for the overall false positive error rate. This enhances the robustness and reproducibility of such findings.