ArticleGenome biology2016
An evaluation of methods correcting for cell-type heterogeneity in DNA methylation studies.
Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
86 citing papers in PubMed, 2 syntheses or guidelines pooled it, 168 citations in OpenAlex.
- DNA methylation studies of depression with onset in the peripartum: A critical systematic review.Neuroscience and biobehavioral reviews · 2019Pooled it
- Case-control meta-analysis of blood DNA methylation and autism spectrum disorder.Molecular autism · 2018Pooled it
- Whole genome methylation and transcriptome analyses to identify risk for cerebral palsy (CP) in extremely low gestational age neonates (ELGAN).Scientific reports · 2021Trial
- Comparison of DNA methylation profiles from saliva in Coeliac disease and non-coeliac disease individuals.BMC medical genomics · 2020Trial
- An epigenetic framework for understanding contextual influences on neural and socio-emotional development: Narrative review and case-study of the oxytocin receptor.Developmental cognitive neuroscience · 2026Review
- Comparison of DNA methylation measured in saliva and peripheral blood as a marker of exposure and outcome: a scoping review.Clinical epigenetics · 2026Article
- Novel epigenetic and transcriptomic profiles of immune, inflammatory, and cellular transduction pathways are associated with chronic perceived stress in midlife women.Brain, behavior, & immunity - health · 2026Article
- Analysis Methods for Diagnosing Rare Neurodevelopmental Diseases with Episignatures: A Systematic Review of the Literature.Biomedicines · 2025Review
- Longitudinal Analysis of Estrogen Receptor Gene Methylation, Estradiol, and Depressive Symptoms During the Perinatal Period.Molecular neurobiology · 2025Article
- Distinct Co-methylation Patterns in African and European Populations and Their Genetic Associations.Genomics, proteomics & bioinformatics · 2025Article
- Article
- A review of the use of tumour DNA methylation for breast cancer subtyping and prediction of outcomes.Clinical epigenetics · 2025Review
- Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies.Bioinformatics (Oxford, England) · 2025Article
- Development and validation of a novel cell type estimation method for targeted bisulfite sequencing data.Epigenomics · 2025Article
- Fast matrix completion in epigenetic methylation studies with informative covariates.Biostatistics (Oxford, England) · 2024Article
- Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics.Science advances · 2024Article
- Peripheral blood DNA methylation and neuroanatomical responses to HDACi treatment that rescues neurological deficits in a Kabuki syndrome mouse model.Clinical epigenetics · 2023Article
- Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes.Nature communications · 2023Article
- Gastrointestinal Symptom Cluster is Associated With Epigenetic Regulation of Lymphotoxin Beta in Oncology Patients Receiving Chemotherapy.Biological research for nursing · 2023Article
- DNA Methylation Changes in Blood Cells of Fibromyalgia and Chronic Fatigue Syndrome Patients.Journal of pain research · 2023Article
26 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundMany different methods exist to adjust for variability in cell-type mixture proportions when analyzing DNA methylation studies. Here we present the result of an extensive simulation study, built on cell-separated DNA methylation profiles from Illumina Infinium 450K methylation data, to compare the performance of eight methods including the most commonly used approaches.
resultsWe designed a rich multi-layered simulation containing a set of probes with true associations with either binary or continuous phenotypes, confounding by cell type, variability in means and standard deviations for population parameters, additional variability at the level of an individual cell-type-specific sample, and variability in the mixture proportions across samples. Performance varied quite substantially across methods and simulations. In particular, the number of false positives was sometimes unrealistically high, indicating limited ability to discriminate the true signals from those appearing significant through confounding. Methods that filtered probes had consequently poor power. QQ plots of p values across all tested probes showed that adjustments did not always improve the distribution. The same methods were used to examine associations between smoking and methylation data from a case-control study of colorectal cancer, and we also explored the effect of cell-type adjustments on associations between rheumatoid arthritis cases and controls.
conclusionsWe recommend surrogate variable analysis for cell-type mixture adjustment since performance was stable under all our simulated scenarios.
Indexed as
Identifiers
What OpenQuestion holds
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.