methylscaper is an R package for visualizing data that jointly profile endogenous methylation and chromatin accessibility (MAPit, NOMe-seq, scNMT-seq, nanoNOMe, etc.). The package offers pre-processing for single-molecule data and accepts input from Bismark (or similar alignment programs) for single-cell data. A common interface for visualizing both data types is constructed by generating ordered representational methylation-state matrices. The package provides a Shiny app to allow for interactive and optimal ordering of the individual DNA molecules to discover methylation patterns, nucleosome positioning, and transcription factor binding.


methylscaper is available for use on a webserver located at and clicking on "Start Shiny App". Also located on the website is easy access to the vignette and example datasets to use.


For local use of methylscaper, it can be installed into R from Bioconductor (using R version > 4.1.0):

if (!requireNamespace("BiocManager", quietly = TRUE))


Alternatively, the version specified by the ref parameter below only requires R >= 4.0 (current stable release).

if (!requireNamespace("devtools", quietly=TRUE))
devtools::install_github("rhondabacher/methylscaper", ref="R4.0")


Note: on Ubuntu, users may need to install libgsl via: sudo apt-get install libgsl-dev

The following packages are required for methylscaper. If installation fails, you may need to manually install the dependencies using the function 'install.packages' for CRAN packages or 'BiocManager::install' for Bioconductor packages.

For any other installation issues/questions please leave a message on our Github Issues.


A preprint of the methylscaper manuscript is now available on bioRxiv.

Running methylscaper

To load the package into R:


To use methylscaper as a Shiny App:


Many more details and examples on how to use the Shiny App or functions directly in R are located in the vignette:


rhondabacher/methylscaper documentation built on Aug. 12, 2021, 11:16 a.m.