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maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks

View ORCID ProfileTareian Cazares, View ORCID ProfileFaiz W. Rizvi, Balaji Iyer, View ORCID ProfileXiaoting Chen, View ORCID ProfileMichael Kotliar, Joseph A. Wayman, Anthony Bejjani, View ORCID ProfileOmer Donmez, View ORCID ProfileBenjamin Wronowski, Sreeja Parameswaran, View ORCID ProfileLeah C. Kottyan, View ORCID ProfileArtem Barski, View ORCID ProfileMatthew T. Weirauch, View ORCID ProfileVB Surya Prasath, View ORCID ProfileEmily R. Miraldi
doi: https://doi.org/10.1101/2022.01.28.478235
Tareian Cazares
1Immunology Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
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Faiz W. Rizvi
2Department of Pharmacology and Systems Biology Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH, 45229, USA
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Balaji Iyer
3Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
4Department of Electrical Engineering and Computer Science, University of Cincinnati, OH 45221, USA
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Xiaoting Chen
5The Center for Autoimmune Genetics and Etiology (CAGE), Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
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Michael Kotliar
6Division of Allergy and Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
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Joseph A. Wayman
7Division of Immunobiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
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Anthony Bejjani
8Molecular and Developmental Biology Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
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Omer Donmez
5The Center for Autoimmune Genetics and Etiology (CAGE), Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
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Benjamin Wronowski
6Division of Allergy and Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
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Sreeja Parameswaran
5The Center for Autoimmune Genetics and Etiology (CAGE), Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
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Leah C. Kottyan
5The Center for Autoimmune Genetics and Etiology (CAGE), Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
9Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
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Artem Barski
6Division of Allergy and Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
9Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
10Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
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Matthew T. Weirauch
3Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
5The Center for Autoimmune Genetics and Etiology (CAGE), Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
9Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
11Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
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VB Surya Prasath
3Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
9Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
4Department of Electrical Engineering and Computer Science, University of Cincinnati, OH 45221, USA
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Emily R. Miraldi
3Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
7Division of Immunobiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 45229, USA
9Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
4Department of Electrical Engineering and Computer Science, University of Cincinnati, OH 45221, USA
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  • For correspondence: emily.miraldi@cchmc.org
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Abstract

Transcription factors read the genome, fundamentally connecting DNA sequence to gene expression across diverse cell types. Determining how, where, and when TFs bind chromatin will advance our understanding of gene regulatory networks and cellular behavior. The 2017 ENCODE-DREAM in vivo Transcription-Factor Binding Site (TFBS) Prediction Challenge highlighted the value of chromatin accessibility data to TFBS prediction, establishing state-of-the-art methods. Yet, while Assay-for-Transposase-Accessible-Chromatin (ATAC)-seq datasets grow exponentially, suboptimal motif scanning is commonly used for TFBS prediction from ATAC-seq. Here, we present “maxATAC”, a suite of user-friendly, deep neural network models for genome-wide TFBS prediction from ATAC-seq in any cell type. With models available for 127 human TFs, maxATAC is the largest collection of state-of-the-art TFBS models to date. maxATAC performance extends to primary cells and single-cell ATAC-seq, enabling state-of-the-art TFBS prediction in vivo. We demonstrate maxATAC’s capabilities by identifying TFBS associated with allele-dependent chromatin accessibility at atopic dermatitis genetic risk loci.

Competing Interest Statement

AB is a co-founder of Datirium, LLC.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted January 29, 2022.
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maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks
Tareian Cazares, Faiz W. Rizvi, Balaji Iyer, Xiaoting Chen, Michael Kotliar, Joseph A. Wayman, Anthony Bejjani, Omer Donmez, Benjamin Wronowski, Sreeja Parameswaran, Leah C. Kottyan, Artem Barski, Matthew T. Weirauch, VB Surya Prasath, Emily R. Miraldi
bioRxiv 2022.01.28.478235; doi: https://doi.org/10.1101/2022.01.28.478235
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maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks
Tareian Cazares, Faiz W. Rizvi, Balaji Iyer, Xiaoting Chen, Michael Kotliar, Joseph A. Wayman, Anthony Bejjani, Omer Donmez, Benjamin Wronowski, Sreeja Parameswaran, Leah C. Kottyan, Artem Barski, Matthew T. Weirauch, VB Surya Prasath, Emily R. Miraldi
bioRxiv 2022.01.28.478235; doi: https://doi.org/10.1101/2022.01.28.478235

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