ArticleEpigenetics2023
Uncertainty quantification of reference-based cellular deconvolution algorithms.
Article in Epigenetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Neuroinflammation as molecular landscape of post-operative delirium revealed by live human brain multi-omics profiling.Molecular psychiatry · 2026Article
- Mechanisms underlying end-organ injury in sleep apnoea.The European respiratory journal · 2026Review
- Setd1a Loss-of-function Disrupts Epigenetic Regulation of Ribosomal Genes via Altered DNA Methylation.Schizophrenia bulletin · 2026Article
- Epigenomic subtypes of late-onset Alzheimer's disease reveal distinct microglial signatures.Acta neuropathologica · 2026Article
- Not all saliva samples are equal: The role of cellular heterogeneity in DNA methylation and epigenetic age analyses with biological and psychosocial factors.Psychoneuroendocrinology · 2026Article
- Cell-type-specific DNA methylation dynamics in the prenatal and postnatal human cortex.Cell genomics · 2025Article
- Interrogating DNA methylation associated with Lewy body pathology in a cross brain-region and multi-cohort study.medRxiv : the preprint server for health sciences · 2025Article
- DNA methylation patterns in the frontal lobe white matter of multiple system atrophy, Parkinson's disease, and progressive supranuclear palsy: a cross-comparative investigation.Acta neuropathologica · 2024Article
- Transcriptome- and DNA methylation-based cell-type deconvolutions produce similar estimates of differential gene expression and differential methylation.BioData mining · 2024Article
- Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics.Science advances · 2024Article
- Transcriptome- and DNA methylation-based cell-type deconvolutions produce similar estimates of differential gene expression and differential methylation.Research square · 2024Article
- Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles.BMC biology · 2024Article
- Examining epigenetic aging in the post-mortem brain in attention deficit hyperactivity disorder.Frontiers in genetics · 2024Article
- Article
- Calculating detection limits and uncertainty of reference-based deconvolution of whole-blood DNA methylation data.Epigenomics · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The majority of epigenetic epidemiology studies to date have generated genome-wide profiles from bulk tissues (e.g., whole blood) however these are vulnerable to confounding from variation in cellular composition. Proxies for cellular composition can be mathematically derived from the bulk tissue profiles using a deconvolution algorithm; however, there is no method to assess the validity of these estimates for a dataset where the true cellular proportions are unknown. In this study, we describe, validate and characterize a sample level accuracy metric for derived cellular heterogeneity variables. The CETYGO score captures the deviation between a sample's DNA methylation profile and its expected profile given the estimated cellular proportions and cell type reference profiles. We demonstrate that the CETYGO score consistently distinguishes inaccurate and incomplete deconvolutions when applied to reconstructed whole blood profiles. By applying our novel metric to >6,300 empirical whole blood profiles, we find that estimating accurate cellular composition is influenced by both technical and biological variation. In particular, we show that when using a common reference panel for whole blood, less accurate estimates are generated for females, neonates, older individuals and smokers. Our results highlight the utility of a metric to assess the accuracy of cellular deconvolution, and describe how it can enhance studies of DNA methylation that are reliant on statistical proxies for cellular heterogeneity. To facilitate incorporating our methodology into existing pipelines, we have made it freely available as an R package (https://github.com/ds420/CETYGO).
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