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Stripenn detects architectural stripes from chromatin conformation data using computer vision

View ORCID ProfileSora Yoon, View ORCID ProfileGolnaz Vahedi
doi: https://doi.org/10.1101/2021.04.16.440239
Sora Yoon
1Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
2Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
3Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
4Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
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  • ORCID record for Sora Yoon
Golnaz Vahedi
1Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
2Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
3Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
4Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
5Abramson Family Cancer Research Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
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  • ORCID record for Golnaz Vahedi
  • For correspondence: vahedi@pennmedicine.upenn.edu
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Abstract

Architectural stripes tend to form at genomic regions harboring genes with salient roles in cell identity and function. Therefore, the accurate identification and quantification of these features is essential for the understanding of lineage-specific gene regulation. Here, we present Stripenn, an algorithm rooted in computer vision to systematically detect and quantitate architectural stripes from chromatin conformation measurements of various technologies. We demonstrate that Stripenn outperforms existing methods, highlight its biological applications in the context of B and T lymphocytes, and examine the role of sequence variation on architectural stripes by studying the conservation of these features in inbred strains of mice. In summary, Stripenn is a computational method which borrows concepts from widely used image processing techniques for demarcation and quantification of architectural stripes.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
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-ND 4.0 International license.
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Posted April 18, 2021.
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Stripenn detects architectural stripes from chromatin conformation data using computer vision
Sora Yoon, Golnaz Vahedi
bioRxiv 2021.04.16.440239; doi: https://doi.org/10.1101/2021.04.16.440239
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Stripenn detects architectural stripes from chromatin conformation data using computer vision
Sora Yoon, Golnaz Vahedi
bioRxiv 2021.04.16.440239; doi: https://doi.org/10.1101/2021.04.16.440239

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