ArticleGenome biology2017
Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable approaches in empirical studies.
Article in Genome biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis 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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude.Clinical epigenetics · 2023Pooled it
- Reference-free deconvolution of complex samples based on cross-cell-type differential analysis: Systematic evaluations with various feature selection options.Frontiers in genetics · 2025Article
- A methylome-wide association study of major depression with out-of-sample case-control classification and trans-ancestry comparison.Nature. Mental health · 2025Article
- Fine-grained cell-type specific association studies with human bulk brain data using a large single-nucleus RNA sequencing based reference panel.Scientific reports · 2023Article
- DNA methylation signatures of childhood trauma predict psychiatric disorders and other adverse outcomes 17 years after exposure.Molecular psychiatry · 2022Article
- A targeted solution for estimating the cell-type composition of bulk samples.BMC bioinformatics · 2021Article
- Deconvolution of heterogeneous tumor samples using partial reference signals.PLoS computational biology · 2020Article
- Methylome-wide association findings for major depressive disorder overlap in blood and brain and replicate in independent brain samples.Molecular psychiatry · 2020Article
- A methylation study of long-term depression risk.Molecular psychiatry · 2020Article
- Cell Type-Specific Methylome-wide Association Studies Implicate Neurotrophin and Innate Immune Signaling in Major Depressive Disorder.Biological psychiatry · 2020Article
- Independent Methylome-Wide Association Studies of Schizophrenia Detect Consistent Case-Control Differences.Schizophrenia bulletin · 2020Article
- Epigenetic aging is accelerated in alcohol use disorder and regulated by genetic variation in APOL2.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2020Article
- Accelerating research on biological aging and mental health: Current challenges and future directions.Psychoneuroendocrinology · 2019Review
- Convergence of evidence from a methylome-wide CpG-SNP association study and GWAS of major depressive disorder.Translational psychiatry · 2018Article
- Epigenetic Aging in Major Depressive Disorder.The American journal of psychiatry · 2018Article
- Statistical and integrative system-level analysis of DNA methylation data.Nature reviews. Genetics · 2018Review
- Maximizing ecological and evolutionary insight in bisulfite sequencing data sets.Nature ecology & evolution · 2017Review
- Article
- Response to: Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable approaches in empirical studies.Genome biology · 2017Article
Corrections and comments
- Commented on by
- Comment on
Authors and funding
15 authors.
Funding
Abstract
Based on an extensive simulation study, McGregor and colleagues recently recommended the use of surrogate variable analysis (SVA) to control for the confounding effects of cell-type heterogeneity in DNA methylation association studies in scenarios where no cell-type proportions are available. As their recommendation was mainly based on simulated data, we sought to replicate findings in two large-scale empirical studies. In our empirical data, SVA did not fully correct for cell-type effects, its performance was somewhat unstable, and it carried a risk of missing true signals caused by removing variation that might be linked to actual disease processes. By contrast, a reference-based correction method performed well and did not show these limitations. A disadvantage of this approach is that if reference methylomes are not (publicly) available, they will need to be generated once for a small set of samples. However, given the notable risk we observed for cell-type confounding, we argue that, to avoid introducing false-positive findings into the literature, it could be well worth making this investment.Please see related Correspondence article: https://genomebiology.biomedcentral.com/articles/10/1186/s13059-017-1149-7 and related Research article: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0935-y.
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.