ArticleGenome biology2018
BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference.
Article in Genome biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Correcting spatial transcriptomics data affected by a prevalent transcript leakage problem across platforms, species, and tissues.bioRxiv : the preprint server for biology · 2026Article
- Multi-Ancestry Epigenome-Wide Meta-Analysis Identifies Novel Bulk and Cell-Type-Specific Epigenetic Markers of Asthma with Severe Exacerbations.medRxiv : the preprint server for health sciences · 2026Article
- UBD: incorporating uncertainty in cell type proportion estimates from bulk samples to infer cell-type-specific profiles.Briefings in bioinformatics · 2026Article
- Unico: a unified model for cell-type resolution genomics from heterogeneous omics data.Genome biology · 2025Article
- Epigenetic patient stratification reveals a sub-endotype of type 2 asthma with altered B-cell response.medRxiv : the preprint server for health sciences · 2025Article
- Computational analysis of DNA methylation from long-read sequencing.Nature reviews. Genetics · 2025Review
- Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations.STAR protocols · 2025Review
- Reference-free deconvolution of complex samples based on cross-cell-type differential analysis: Systematic evaluations with various feature selection options.Frontiers in genetics · 2025Article
- HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data.Genome biology · 2024Article
- Epigenetic patient stratification via contrastive machine learning refines hallmark biomarkers in minoritized children with asthma.Research square · 2024Article
- Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis.Cancer research · 2024Article
- Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges.Nucleic acids research · 2024Review
- Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors.Nature communications · 2024Article
- Computational deconvolution of DNA methylation data from mixed DNA samples.Briefings in bioinformatics · 2024Review
- Challenges and perspectives in computational deconvolution of genomics data.Nature methods · 2024Review
- EpiMix is an integrative tool for epigenomic subtyping using DNA methylation.Cell reports methods · 2023Article
- Hydroxymethylation alterations in progenitor-like cell types of pediatric central nervous system tumors are associated with cell type-specific transcriptional changes.Research square · 2023Article
- CeDAR: incorporating cell type hierarchy improves cell type-specific differential analyses in bulk omics data.Genome biology · 2023Article
- EpiMix: an integrative tool for epigenomic subtyping using DNA methylation.bioRxiv : the preprint server for biology · 2023Article
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Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
We introduce a Bayesian semi-supervised method for estimating cell counts from DNA methylation by leveraging an easily obtainable prior knowledge on the cell-type composition distribution of the studied tissue. We show mathematically and empirically that alternative methods which attempt to infer cell counts without methylation reference only capture linear combinations of cell counts rather than provide one component per cell type. Our approach allows the construction of components such that each component corresponds to a single cell type, and provides a new opportunity to investigate cell compositions in genomic studies of tissues for which it was not possible before.
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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.