Evidence map›Paper›PMID 41883158›Full record

ArticleBioinformatics (Oxford, England)2026

CpGene: a web application for epigenetic signature identification from DNA methylation arrays.

Konstantinos Lazaros, Souzana Logotheti, Christopher Logothetis, Vasiliki Tzelepi, Panagiotis Vlamos, Aristidis G Vrahatis

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Konstantinos LazarosBioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu 49100, Greece.ORCID 0000-0002-9527-3946
Souzana LogothetiDepartment of Pathology, School of Medicine, University of Patras, Patras 26504, Greece.
Christopher LogothetisDepartment of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, United States.
Vasiliki TzelepiDepartment of Pathology, School of Medicine, University of Patras, Patras 26504, Greece.
Panagiotis VlamosBioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu 49100, Greece.
Aristidis G VrahatisBioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu 49100, Greece.

Funding

National Science Foundation and Ronald and Rita McAulay Foundation (RRMF) 82690
6 · The paper itself

Abstract

motivationDNA methylation (DNAme) is the best studied epigenetic mechanism that plays pivotal role in tissue differentiation and epigenetic disruption has been correlated to diverse disease types (e.g. cancer, metabolic disorders). While various DNAme array platforms have been discovered, data analysis remains a challenging task which often requires in-depth bioinformatic expertise. Here, we developed a user-friendly web-based application for data analysis and visualization that accommodates users ranging from early-career basic/translational researchers to experienced bioinformaticians.

resultsCpGene is a web application for analyzing DNA methylation array data. It supports Illumina 450K, EPIC, and EPICv2 methylation array platforms and processes .idat files with integrated preprocessing, normalization, and quality control. Biomarker discovery is available through either classic differential methylation point analysis or machine learning-based feature selection as well as gene enrichment analysis. Results are summarized with clear visualizations, to aid interpretation. By combining these functions in a unified interface, CpGene streamlines methylation analysis and helps identify CpG sites and genes with biological and clinical relevance. AVAILABILITY AND IMPLEMENTATION: CpGene is openly accessible as a web service through http://cpgene.duckdns.org:8001/ and it's source code is available on https://github.com/kostaslazaros/cpgenene.

Indexed as

DNA MethylationEpigenesis, GeneticEpigenomicsOligonucleotide Array Sequence AnalysisSoftwareComputational BiologyCpG IslandsHumansInternet

Identifiers

PMID41883158
PMCPMC13141144

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.