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methylscaper: an R/Shiny app for joint visualization of DNA methylation and nucleosome occupancy in single-molecule and single-cell data

Parker Knight, Marie-Pierre L. Gauthier, Carolina E. Pardo, Russell P. Darst, Alberto Riva, Michael P. Kladde, View ORCID ProfileRhonda Bacher
doi: https://doi.org/10.1101/2020.11.13.382465
Parker Knight
1Department of Biostatistics, University of Florida, Gainesville, FL
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Marie-Pierre L. Gauthier
2Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL
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Carolina E. Pardo
2Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL
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Russell P. Darst
2Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL
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Alberto Riva
3Bioinformatics Core, Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, Florida
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Michael P. Kladde
2Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL
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Rhonda Bacher
1Department of Biostatistics, University of Florida, Gainesville, FL
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  • ORCID record for Rhonda Bacher
  • For correspondence: rbacher@ufl.edu
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Abstract

Differential DNA methylation and chromatin accessibility are associated with disease development, particularly cancer. Methods that allow profiling of these epigenetic mechanisms in the same reaction and at the single-molecule or single-cell level continue to emerge. However, a challenge lies in jointly visualizing and analyzing the heterogeneous nature of the data and extracting regulatory insight. Here, we developed methylscaper, a visualization framework for simultaneous analysis of DNA methylation and chromatin landscapes. Methylscaper implements a weighted principle component analysis that orders sequencing reads, each providing a record of the chromatin state of one epiallele, and reveals patterns of nucleosome positioning, transcription factor occupancy, and DNA methylation. We demonstrate methylscaper’s utility on a long-read, single-molecule methyltransferase accessibility protocol for individual templates (MAPit) dataset and a single-cell nucleosome, methylation, and transcription sequencing (scNMT-seq) dataset. In comparison to other procedures, methylscaper is able to readily identify chromatin features that are biologically relevant to transcriptional status while scaling to larger datasets.

Availability and implementation Methylscaper, is available on GitHub at https://github.com/rhondabacher/methylscaper.

Contact rbacher{at}ufl.edu

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/rhondabacher/methylscaper

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 4.0 International license.
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Posted November 15, 2020.
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methylscaper: an R/Shiny app for joint visualization of DNA methylation and nucleosome occupancy in single-molecule and single-cell data
Parker Knight, Marie-Pierre L. Gauthier, Carolina E. Pardo, Russell P. Darst, Alberto Riva, Michael P. Kladde, Rhonda Bacher
bioRxiv 2020.11.13.382465; doi: https://doi.org/10.1101/2020.11.13.382465
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methylscaper: an R/Shiny app for joint visualization of DNA methylation and nucleosome occupancy in single-molecule and single-cell data
Parker Knight, Marie-Pierre L. Gauthier, Carolina E. Pardo, Russell P. Darst, Alberto Riva, Michael P. Kladde, Rhonda Bacher
bioRxiv 2020.11.13.382465; doi: https://doi.org/10.1101/2020.11.13.382465

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