ArticleNAR genomics and bioinformatics2023
Cell type deconvolution of methylated cell-free DNA at the resolution of individual reads.
Article in NAR genomics and bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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The trial behind it
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Who cites it
16 citing papers in PubMed.
- Cell-Specific DNA Methylation Markers in Plasma cfDNA Reveal Diagnostic Potential for Head and Neck Cancer.Journal of Cancer · 2026Article
- Article
- Cell type inference in cell-free nucleic acid liquid biopsy.Nature biotechnology · 2025Review
- Read-level DNA methylation deconvolution enhances circulating tumor DNA detection.Briefings in bioinformatics · 2025Article
- Epigenetic Profiling of Cell-Free DNA in Cerebrospinal Fluid: A Novel Biomarker Approach for Metabolic Brain Diseases.Life (Basel, Switzerland) · 2025Review
- Circulating cell-free DNA methylation patterns indicate cellular sources of allograft injury after liver transplant.Nature communications · 2025Article
- cfTools: an R/Bioconductor package for deconvolving cell-free DNA via methylation analysis.Bioinformatics advances · 2025Article
- Cell-Free DNA, a Noninvasive Biomarker for Prediction and Detection of Neurodegenerative Diseases, New Insights, and Perspectives.CNS & neurological disorders drug targets · 2025Review
- Systematic evaluation of methylation-based cell type deconvolution methods for plasma cell-free DNA.Genome biology · 2024Article
- MetDecode: methylation-based deconvolution of cell-free DNA for noninvasive multi-cancer typing.Bioinformatics (Oxford, England) · 2024Article
- CelFiE-ISH: a probabilistic model for multi-cell type deconvolution from single-molecule DNA methylation haplotypes.Genome biology · 2024Article
- Benchmarking of methods for DNA methylome deconvolution.Nature communications · 2024Article
- Circulating, cell-free methylated DNA indicates cellular sources of allograft injury after liver transplant.bioRxiv : the preprint server for biology · 2024Article
- Computational deconvolution of DNA methylation data from mixed DNA samples.Briefings in bioinformatics · 2024Review
- A Novel Tissue-Free Method to Estimate Tumor-Derived Cell-Free DNA Quantity Using Tumor Methylation Patterns.Cancers · 2023Article
- Unlocking the secrets: the power of methylation-based cfDNA detection of tissue damage in organ systems.Clinical epigenetics · 2023Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that are detectable in bodily fluids, such as the plasma. Accelerated cell death, for example caused by disease, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA molecules can provide information about an individual's health. In this work, we aim to increase the sensitivity of methylation-based cell type deconvolution by adapting an existing method, CelFiE, which uses the methylation beta values of individual CpG sites to estimate cell type proportions. Our new method, CelFEER, instead differentiates cell types by the average methylation values within individual reads. We additionally improved the originally reported performance of CelFiE by using a new approach for finding marker regions that are differentially methylated between cell types. We show that CelFEER estimates cell type proportions with a higher correlation (
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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.