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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.

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Prediction of Enhancer–Gene Interactions Using Chromatin-Conformation Capture and Epigenome Data Using STARE

  • 实验方案

  • 发表日期：

    2025年

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  • Dennis Hecker,
  • Marcel H. Schulz

摘要

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.