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

Author:

Knight Parker1,Gauthier Marie-Pierre L2,Pardo Carolina E2,Darst Russell P2,Kapadia Kevin3,Browder Hadley3,Morton Eliza3,Riva Alberto4ORCID,Kladde Michael P2,Bacher Rhonda1ORCID

Affiliation:

1. Department of Biostatistics, University of Florida, Gainesville, FL, USA

2. Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA

3. Department of Statistics, University of Florida, Gainesville, FL, USA

4. Bioinformatics Core, Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, USA

Abstract

Abstract Summary 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 present methylscaper, a visualization framework for simultaneous analysis of DNA methylation and chromatin accessibility landscapes. Methylscaper implements a weighted principal component analysis that orders DNA molecules, 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-BGS) 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 implemented in R (version > 4.1) and available on Bioconductor: https://bioconductor.org/packages/methylscaper/, GitHub: https://github.com/rhondabacher/methylscaper/, and Web: https://methylscaper.com. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

University of Florida Health Cancer Center

National Institutes of Health

Defense Threat Reduction Agency

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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