MethylMix: an R Package for Identifying DNA Methylation-driven Genes

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2015 Jan 23

PMID 25609794

Citations 88

Authors

Olivier Gevaert

Affiliations

Soon will be listed here.

Abstract

Unlabelled: DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is an alternative mechanism to deregulate gene expression in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. Yet, few tools exist that can formally identify hypo and hypermethylated genes that are predictive of transcription and thus functionally relevant for a particular disease. To accommodate this lack of tools, we developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes. MethylMix is based on a beta mixture model to identify methylation states and compares them with the normal DNA methylation state. MethylMix introduces a novel metric, the 'Differential Methylation value' or DM-value defined as the difference of a methylation state with the normal methylation state. Finally, matched gene expression data are used to identify, besides differential, transcriptionally predictive methylation states by focusing on methylation changes that effect gene expression.

Availability And Implementation: MethylMix was implemented as an R package and is available in bioconductor.

Citing Articles

Development of a prognostic model for early-stage gastric cancer-related DNA methylation-driven genes and analysis of immune landscape.

Su C, Lin Z, Ye Z, Liang J, Yu R, Wan Z Front Mol Biosci. 2024; 11:1455890.

PMID: 39575189 PMC: 11579923. DOI: 10.3389/fmolb.2024.1455890.

Integrated analysis of methylation and transcriptome identifies a novel risk model for diagnosis, prognosis, and immune characteristics in head and neck squamous cell carcinoma.

Zhang J, Gao X, Li S, Zhuang S, Liang Q Mol Genet Genomics. 2024; 299(1):71.

PMID: 39031208 DOI: 10.1007/s00438-024-02164-z.

Analysis of methylation-driven genes for predicting the prognosis of patients with oral squamous cell carcinoma.

Chen J, Dong Z, Li B, Nie Z, Qiu J Transl Cancer Res. 2024; 13(6):2892-2904.

PMID: 38988925 PMC: 11231807. DOI: 10.21037/tcr-23-2303.

Comprehensive data mining reveals RTK/RAS signaling pathway as a promoter of prostate cancer lineage plasticity through transcription factors and CNV.

Wei G, Zhang X, Liu S, Hou W, Dai Z Sci Rep. 2024; 14(1):11688.

PMID: 38778150 PMC: 11111877. DOI: 10.1038/s41598-024-62256-z.

Abnormal methylation mediated upregulation of LINC00857 boosts malignant progression of lung adenocarcinoma by modulating the miR-486-5p/NEK2 axis.

Fu H, Zhang M, Liu X, Yang Y, Xing Y Clin Respir J. 2024; 18(5):e13765.

PMID: 38721812 PMC: 11079885. DOI: 10.1111/crj.13765.

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