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WhichTF is dominant in your open chromatin data?

View ORCID ProfileYosuke Tanigawa, Ethan S. Dyer, View ORCID ProfileGill Bejerano
doi: https://doi.org/10.1101/730200
Yosuke Tanigawa
1Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
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Ethan S. Dyer
2Stanford Institute for Theoretical Physics, Stanford University, Stanford, CA, USA
3Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD, USA
7Google, Mountain View, CA, USA
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Gill Bejerano
1Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, USA
4Department of Developmental Biology, Stanford University, Stanford, CA, USA
5Department of Computer Science, Stanford University, Stanford, CA, USA
6Department of Pediatrics, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
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  • For correspondence: bejerano@stanford.edu
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Abstract

We present WhichTF, a novel computational method to identify dominant transcription factors (TFs) from chromatin accessibility measurements. To rank TFs, WhichTF integrates high-confidence genome-wide computational prediction of TF binding sites based on evolutionary sequence conservation, putative gene-regulatory models, and ontology-based gene annotations. Applying WhichTF, we find that the identified dominant TFs have been implicated as functionally important in well-studied cell types, such as NF-κB family members in lymphocytes and GATA factors in cardiac tissue. To distinguish the transcriptional regulatory landscape in closely related samples, we devise a differential analysis framework and demonstrate its utility in lymphocyte, mesoderm developmental, and disease cells. We also find TFs known for stress response in multiple samples, suggesting routine experimental caveats that warrant careful consideration. WhichTF yields biological insight into known and novel molecular mechanisms of TF-mediated transcriptional regulation in diverse contexts, including human and mouse cell types, cell fate trajectories, and disease-associated tissues.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted August 20, 2019.
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WhichTF is dominant in your open chromatin data?
Yosuke Tanigawa, Ethan S. Dyer, Gill Bejerano
bioRxiv 730200; doi: https://doi.org/10.1101/730200
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WhichTF is dominant in your open chromatin data?
Yosuke Tanigawa, Ethan S. Dyer, Gill Bejerano
bioRxiv 730200; doi: https://doi.org/10.1101/730200

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