A two-sample tree-based test for hierarchically organized genomic signals
本文针对基因组研究中沿线性染色体分层组织的信号数据，提出一种基于树表示的双样本检验框架，利用树距离和叶对聚合过程评估不同生物条件下基因组矩阵的差异显著性，数值实验和真实数据（GWAS、Hi-C）验证了其准确性和统计功效。
Abstract This article addresses a common type of data encountered in genomic studies, where a signal along a linear chromosome exhibits a hierarchical organization. We propose a novel framework to assess the significance of dissimilarities between two sets of genomic matrices obtained from distinct biological conditions. Our approach relies on a data representation based on trees. It utilizes tree distances and an aggregation procedure for tests performed at the level of leaf pairs. Numerical experiments demonstrate its statistical validity and its superior accuracy and power compared to alternatives. The method’s effectiveness is illustrated using real-world data from GWAS and Hi-C data.