Institute for Computational Genomic Medicine and Institute of Cardiovascular Regeneration, Goethe University Frankfurt am Main, Frankfurt, Germany.
Methods Mol Biol. 2025;2856:327-339. doi: 10.1007/978-1-0716-4136-1_20.
Disentangling the relationship of enhancers and genes is an ongoing challenge in epigenomics. We present STARE, our software to quantify the strength of enhancer-gene interactions based on enhancer activity and chromatin contact data. It implements the generalized Activity-by-Contact (gABC) score, which allows predicting putative target genes of candidate enhancers over any desired genomic distance. The only requirement for its application is a measurement of enhancer activity. In addition to regulatory interactions, STARE calculates transcription factor (TF) affinities on gene level. We illustrate its usage on a public single-cell data set of the human heart by predicting regulatory interactions on cell type level, by giving examples on how to integrate them with other data modalities, and by constructing TF affinity matrices.
解析增强子和基因之间的关系是表观基因组学中的一个持续挑战。我们提出了 STARE，这是一款用于根据增强子活性和染色质接触数据来量化增强子-基因相互作用强度的软件。它实现了广义的活性-接触（gABC）评分，该评分允许在任何期望的基因组距离上预测候选增强子的潜在靶基因。其应用的唯一要求是测量增强子活性。除了调控相互作用外，STARE 还在基因水平上计算转录因子（TF）亲和力。我们通过在细胞类型水平上预测调控相互作用，举例说明了如何将其与其他数据模式集成，并构建了 TF 亲和力矩阵，在人类心脏的公共单细胞数据集上说明了其用法。
