ReviewBriefings in bioinformatics2024
Computational deconvolution of DNA methylation data from mixed DNA samples.
Review in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The trial behind it
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Who cites it
12 citing papers in PubMed.
- TET1-mediated DNA demethylation and transcription activation of MRPS17 induces lung adenocarcinoma through PI3K-AKT-mTOR pathway.Journal of molecular histology · 2026Article
- Placental molecular subtypes of severe preeclampsia reveal divergent aging trajectories and fetal growth outcomes.medRxiv : the preprint server for health sciences · 2026Article
- DNA methylation heterogeneity in complex tumor microenvironment: Quantitative methods, influencing factors, and clinical implications.Genes & diseases · 2026Review
- DNA methylation is associated with von Willebrand factor and coagulation factor VIII plasma levels: the atherosclerosis risk in communities study.Clinical epigenetics · 2026Article
- Evaluating and Optimizing Mass Spectrometry Proteomics Data to Deconvolve Cell-Type-Specific Protein Expression in Tumors.Journal of proteome research · 2026Article
- Investigation of a global mouse methylome atlas reveals subtype-specific copy number alterations in pediatric cancer models.Nature genetics · 2026Article
- Genetic Deconvolution of Embryonic and Maternal Cell-Free DNA in Spent Culture Medium of Human Preimplantation Embryo Through Deep Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Artificial intelligence for comprehensive DNA methylation analysis: overview, challenges, and future directions.Briefings in bioinformatics · 2025Review
- Read-level DNA methylation deconvolution enhances circulating tumor DNA detection.Briefings in bioinformatics · 2025Article
- Fourier Spectral Deconvolution to Describe Behaviors of pH-Dependent Monomeric and Self-Associated Anthocyanin Species.Journal of chemical information and modeling · 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
- DNA methylation-based analysis reveals accelerated epigenetic aging in giant cell-enriched adult-type glioblastoma.Clinical epigenetics · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.
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Registered trials
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.