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Transcription Factor Activity and Gene Regulatory Networks From Single-Cell ATAC, Gene Expression and ChIP-Seq Using Epiregulon [ASHG 2026]

Transcription factors (TFs) regulate gene expression programs underlying cell identity and function. Direct profiling of TF binding in individual cells remains technically challenging, but advances in single-cell multiomics and computational analysis now enable inference of TF activity and regulatory networks. Here, we integrate 10X Genomics Single-Cell Multiome (scRNA-seq and scATAC-seq) data with curated public ChIP-Seq datasets using Epiregulon and Omabit analysis to infer TF activity and gene regulatory networks. We analyzed human PBMCs and mouse brain, focusing on monocytes and microglia, two related myeloid populations with distinct developmental origins. Omabit’s curated ChIP-Seq integration approximately doubled the proportion of predicted TF binding sites independently confirmed by ChIP-Seq compared with the standard ChIP-Atlas that comes packaged with Epiregulon.

Together, these results demonstrate how integrating Single-Cell Multiome data with curated TF binding information can reveal shared and distinct regulatory programs across cell populations.

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