Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Event . 2025
License: http://opensource.org/licenses/MIT
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Event . 2025
License: http://opensource.org/licenses/MIT
Data sources: ZENODO
ZENODO
Event . 2025
License: https://opensource.org/licenses/MIT
Data sources: Datacite
ZENODO
Event . 2025
License: https://opensource.org/licenses/MIT
Data sources: Datacite
ZENODO
Event . 2025
License: https://opensource.org/licenses/MIT
Data sources: Datacite
 View all 3 versions
Claim

dmeth: A comprehensive Python toolkit for differential DNA methylation analysis with empirical Bayes moderation and biomarker discovery

appsOther research productkeyboard_double_arrow_right Event 23 Nov 2025Embargo end date: 22 Nov 2025 English Publisher:Zenodo
Authors: Afolabi, Dare;

doi: 10.5281/zenodo.17685513 , 10.5281/zenodo.17777500 , 10.5281/zenodo.17777501

dmeth: A comprehensive Python toolkit for differential DNA methylation analysis with empirical Bayes moderation and biomarker discovery

Abstract

A fast, statistically rigorous Python framework, dmeth implements the full modern differential methylation pipeline - from raw beta matrices to biomarkers and functional interpretation, all in pure Python.

Keywords

FOS: Computer and information sciences, Bioinformatics, Data Science, Bayes Theorem, DNA Methylation, Bayesian statistics, Biomarker Discovery, Differential Methylation, Biomarkers, Tumor, Study Planning, Epigenetics, Cell-type Deconvolution, Python

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average