ArticleBMC genomics2017
Fast and robust adjustment of cell mixtures in epigenome-wide association studies with SmartSVA.
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 1 of them a synthesis that pooled it.
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Who cites it
60 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-analysis of pre-pregnancy maternal body mass index and placental DNA methylation identifies 27 CpG sites with implications for mother-child health.Communications biology · 2022Pooled it
- Genomic Response to Vitamin D Supplementation in the Setting of a Randomized, Placebo-Controlled Trial.EBioMedicine · 2018Trial
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- Prenatal antifungal exposure disrupts fetal steroidogenesis and is associated with persistent effects in children.Communications medicine · 2026Article
- DNA methylation and gene expression signatures for common childhood infections.Clinical epigenetics · 2026Article
- Epigenetic Signatures in Monozygotic and Dizygotic Twins Discordant for Orofacial Clefts.medRxiv : the preprint server for health sciences · 2026Article
- Time-Dependent Glucocorticoid-Induced Transcriptomic Changes in Human Trabecular Meshwork and Schlemm's Canal Cells.Investigative ophthalmology & visual science · 2026Article
- Butterfly brains change in morphology and in gene splicing patterns after brief pheromone exposure.BMC biology · 2026Article
- Time-dependent Glucocorticoid-Induced Transcriptomic Changes in Human Trabecular Meshwork and Schlemm's Canal.bioRxiv : the preprint server for biology · 2026Article
- Analysis Methods for Diagnosing Rare Neurodevelopmental Diseases with Episignatures: A Systematic Review of the Literature.Biomedicines · 2025Review
- Discovery of placental microRNAs associated with maternal insulin sensitivity during pregnancy.Placenta · 2025Article
- Trace element-linked DNA methylation sites and their association with type 2 diabetes and cardiovascular diseases: EPIC-Potsdam cohort study.Clinical epigenetics · 2025Article
- The genetic influence of sex on gene expression for blood in pigs.BMC genomics · 2025Article
- A Machine-Learning Approach Identifies Rejuvenating Interventions in the Human Brain.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- DNA methylation associations with cognitive function in early-stage hormone receptor-positive breast cancer patients.Epigenomics · 2025Article
- Analysis of sex-differential gene expression on the target of approved drug.Scientific reports · 2025Article
- Caregiver-child interaction and early childhood development among preschool children in rural China: the possible role of blood epigenome-wide DNA methylation.BMC genomics · 2025Article
- Article
- Decidual/placental and first trimester plasma levels of hsa-miR-199a-3p|hsa-miR-199b-3p and hsa-miR-3150b-3p are associated with insulin secretion in pregnancy.Frontiers in endocrinology · 2025Article
- Attenuated sex-related DNA methylation differences in cancer highlight the magnitude bias mediating existing disparities.Biology of sex differences · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundOne problem that plagues epigenome-wide association studies is the potential confounding due to cell mixtures when purified target cells are not available. Reference-free adjustment of cell mixtures has become increasingly popular due to its flexibility and simplicity. However, existing methods are still not optimal: increased false positive rates and reduced statistical power have been observed in many scenarios.
methodsWe develop SmartSVA, an optimized surrogate variable analysis (SVA) method, for fast and robust reference-free adjustment of cell mixtures. SmartSVA corrects the limitation of traditional SVA under highly confounded scenarios by imposing an explicit convergence criterion and improves the computational efficiency for large datasets.
resultsCompared to traditional SVA, SmartSVA achieves an order-of-magnitude speedup and better false positive control. It protects the signals when capturing the cell mixtures, resulting in significant power increase while controlling for false positives. Through extensive simulations and real data applications, we demonstrate a better performance of SmartSVA than the existing methods.
conclusionsSmartSVA is a fast and robust method for reference-free adjustment of cell mixtures for epigenome-wide association studies. As a general method, SmartSVA can be applied to other genomic studies to capture unknown sources of variability.
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