Skip to content

DNA methylation analysis downstream to Nanopolish for Oxford Nanopore DNA sequencing datasets

License

Notifications You must be signed in to change notification settings

DrownedMala/pycoMeth

 
 

Repository files navigation

pycoMeth

GitHub license Language DOI

PyPI version PyPI downloads Anaconda Version Anaconda Downloads


Version in this branch: 2.0.1


DNA methylation analysis downstream to Nanopolish for Oxford Nanopore DNA sequencing datasets

pycoMeth can be used for further analyses starting from the output files generated by Nanopolish call-methylation. The package contains a suite of tools to find CpG islands, segment methylome, and to perform a differential methylation analysis across multiple samples.

pycoMeth generates extensive tabulated reports and BED files which can be loaded in a genome browser. In addition, an interactive HTML report of differentially methylated intervals/islands can also generated at the end of the analysis.

Methplotlib developed by Wouter de coster is an excellent complementary tool to visualise and explore methylation status for specific loci.

Please be aware that pycoMeth is a research package that is still under development. The API, command line interface, and implementation might change without retro-compatibility.


Installation

Install either using conda:

conda install -c snajder-r -c bioconda pycometh

Or using pip:

pip install pycometh

pycoMeth workflow

Workflow

pycoMeth example output IGV rendering

IGV

pycoMeth example HTML report

Example HTML report 1

Example HTML report 2

HTML


Citing

The repository is archived at Zenodo. If you use pycoMeth version 2, please cite as follow:

Rene Snajder. (2021, May 18). snajder-r/pycoMeth. Zenodo. https://doi.org/10.5281/zenodo.4772051

For version 1, please cite as:

Adrien Leger. (2020, January 28). a-slide/pycoMeth. Zenodo. https://doi.org/10.5281/zenodo.3629254

Authors and contributors

About

DNA methylation analysis downstream to Nanopolish for Oxford Nanopore DNA sequencing datasets

Resources

License

Code of conduct

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 93.2%
  • Jinja 5.9%
  • Shell 0.9%