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Abstract Transcription factors (TFs) and transcriptional coregulators are emerging therapeutic targets. Gene regulatory networks (GRNs) can evaluate pharmacological agents and identify drivers of disease, but methods that rely solely on gene expression often neglect post-transcriptional modulation of TFs. We present Epiregulon, a method that constructs GRNs from single-cell ATAC-seq and RNA-seq data for accurate prediction of TF activity.
1Division of Hematology/Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA 2Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA 3Department of Immunobiology, University of Lausanne, Epalinges, Switzerland 4Graduate Program in Cellular and Molecular Biology, University of Michigan, Ann Arbor, MI, USA 5Immunology Graduate Group, University of Pennsylvania, Philadelphia, PA, USA 6Children’s Hospital of Philadelphia,...
1Division of Hematology/Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA 2Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA 3Department of Immunobiology, University of Lausanne, Epalinges, Switzerland 4Graduate Program in Cellular and Molecular Biology, University of Michigan, Ann Arbor, MI, USA 5Immunology Graduate Group, University of Pennsylvania, Philadelphia, PA, USA 6Children’s Hospital of Philadelphia,...
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