ArticleGenome biology2017
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
Article in Genome biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03941496 (Phase 1b/2a Safety and Immunogenicity of the DNMT Inhibitor Azacitidine During Anti-Tuberculosis Therapy), which is not on this map. Cited by 56 papers.
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Phase 1b/2a Safety and Immunogenicity of the DNMT Inhibitor Azacitidine During Anti-Tuberculosis Therapy
Who cites it
56 citing papers in PubMed.
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- DNA Methylation-Based Classification of Kidney Neoplasms.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025Article
- Brain DNA Methylation Atlas of AppAging cell · 2025Article
- DNA methylation patterns facilitate tracing the origin of neuroendocrine neoplasms.Nature communications · 2025Article
- DNA methylation analysis reveals an epigenetic signature distinctive of high-grade oligodendroglioma.Acta neuropathologica · 2025Article
- Evidence of DNA methylation heterogeneity and epipolymorphism in kidney cancer tissue samples.Oncogene · 2025Article
- Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations.STAR protocols · 2025Review
- Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity.Cell & bioscience · 2025Article
- Reference-free deconvolution of complex samples based on cross-cell-type differential analysis: Systematic evaluations with various feature selection options.Frontiers in genetics · 2025Article
- MetDecode: methylation-based deconvolution of cell-free DNA for noninvasive multi-cancer typing.Bioinformatics (Oxford, England) · 2024Article
- Computational deconvolution of DNA methylation data from mixed DNA samples.Briefings in bioinformatics · 2024Review
- Identification of region-specific gene isoforms in the human brain using long-read transcriptome sequencing.Science advances · 2024Article
- DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data.Bioinformatics advances · 2024Article
- EpiMix is an integrative tool for epigenomic subtyping using DNA methylation.Cell reports methods · 2023Article
- EpiMix: an integrative tool for epigenomic subtyping using DNA methylation.bioRxiv : the preprint server for biology · 2023Article
- Ageing-associated small RNA cargo of extracellular vesicles.RNA biology · 2023Article
- DNA methylation profiling of central nervous system hemangioblastomas identifies two distinct subgroups.Brain pathology (Zurich, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is important for large-scale epigenomic studies to determine and explore the nature of hidden confounding variation, most importantly cell composition. We developed MeDeCom as a novel reference-free computational framework that allows the decomposition of complex DNA methylomes into latent methylation components and their proportions in each sample. MeDeCom is based on constrained non-negative matrix factorization with a new biologically motivated regularization function. It accurately recovers cell-type-specific latent methylation components and their proportions. MeDeCom is a new unsupervised tool for the exploratory study of the major sources of methylation variation, which should lead to a deeper understanding and better biological interpretation.
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