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Abante, JordiCorresponding Author
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CpelTdm.jl: a Julia package for targeted differential DNA methylation analysis

Publicated to: - 2020-10-18 (), DOI: 10.1101/2020.10.17.343020

Authors: Jordi Abante; John Goutsias

Affiliations

Johns Hopkins University - Author

Abstract

AbstractMotivationIdentifying regions of the genome that demonstrate significant differences in DNA methylation between groups of samples is an important problem in computational epigenetics. Available methods assume that methylation occurs in a statistically independent manner at individual cytosine-phosphate-guanine (CpG) sites or perform analysis using empirically estimated joint probability distributions of methylation patterns at no more than 4 contiguous CpG sites. These approaches can lead to poor detection performance and loss of reliability and reproducibility due to reduced specificity and sensitivity in the presence of insufficient data.ResultsTo accommodate data obtained with different bisulfite sequencing technologies, such as RRBS, ERRBS, and WGBS, and improve statistical power, we developed CpelTdm.jl, a Julia package for targeted differential analysis of DNA methylation stochasticity between groups of unmatched or matched samples. This package performs rigorous statistical analysis of methylation patterns within regions of the genome specified by the user that takes into account correlations in methylation and results in robust detection of genomic regions exhibiting statistically significant differences in methylation stochasticity. CpelTdm.jl does not only detect mean methylation differences, as it is commonly done by previous methods, but also differences in methylation entropy and, more generally, between probability distributions of methylation.Availability and ImplementationThis Julia package is supported for Windows, MacOS, and Linux, and can be freely downloaded from GitHub: https://github.com/jordiabante/CpelTdm.jl.Contactsjabante1@jhu.edu or goutsias@jhu.edu.

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Quality index

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-15:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 4.

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 3.6.
  • The number of mentions on the social network X (formerly Twitter): 8 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: United States of America.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Abante Llenas, Jordi) .

the author responsible for correspondence tasks has been Abante Llenas, Jordi.