ArticlePLoS genetics2015
A Flexible, Efficient Binomial Mixed Model for Identifying Differential DNA Methylation in Bisulfite Sequencing Data.
Article in PLoS genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
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64 citing papers in PubMed.
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- Canon enables causal inference of downstream genes in single-cell CRISPR studies via instrumental variable analysis.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Non-Invasive Measures of DNA Methylation Capture Molecular Aging in Wild Capuchin Monkeys.Molecular ecology · 2026Article
- Uncovering alterations in cancer epigenetics via trans-dimensional Markov chain Monte Carlo and hidden Markov models.Journal of the Royal Statistical Society. Series C, Applied statistics · 2026Article
- Admixture influences the genetic architecture of DNA methylation in a wild primate hybrid zone.Genome biology · 2026Article
- Mapping DNA methylation to cardiac pathologies induced by beta-adrenergic stimulation in a large panel of mice.Epigenetics · 2025Article
- Genetic Architecture of Immune Cell DNA Methylation in the Rhesus Macaque.Molecular ecology · 2025Article
- SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection.Genome biology · 2025Article
- Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing.PLoS genetics · 2025Article
- Immune gene regulation is associated with age and environmental adversity in a nonhuman primate.Molecular ecology · 2024Article
- DNA Methylation Carries Signatures of Sublethal Effects Under Thermal Stress in Loggerhead Sea Turtles.Evolutionary applications · 2024Article
- DNA methylation signatures of early-life adversity are exposure-dependent in wild baboons.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Epigenetic changes to gene pathways linked to male fertility in ex situ black-footed ferrets.Evolutionary applications · 2024Article
- DNA methylation signatures of early life adversity are exposure-dependent in wild baboons.bioRxiv : the preprint server for biology · 2023Article
- Cardiomyocyte ploidy is dynamic during postnatal development and varies across genetic backgrounds.Development (Cambridge, England) · 2023Article
- Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples.Epigenetics · 2022Article
- Spatially aware dimension reduction for spatial transcriptomics.Nature communications · 2022Article
- Orang Asli Health and Lifeways Project (OA HeLP): a cross-sectional cohort study protocol.BMJ open · 2022Article
- Loss of key endosymbiont genes may facilitate early host control of the chromatophore iniScience · 2022Article
4 more citing papers are in PubMed but not listed here.
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3 authors.
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Abstract
Identifying sources of variation in DNA methylation levels is important for understanding gene regulation. Recently, bisulfite sequencing has become a popular tool for investigating DNA methylation levels. However, modeling bisulfite sequencing data is complicated by dramatic variation in coverage across sites and individual samples, and because of the computational challenges of controlling for genetic covariance in count data. To address these challenges, we present a binomial mixed model and an efficient, sampling-based algorithm (MACAU: Mixed model association for count data via data augmentation) for approximate parameter estimation and p-value computation. This framework allows us to simultaneously account for both the over-dispersed, count-based nature of bisulfite sequencing data, as well as genetic relatedness among individuals. Using simulations and two real data sets (whole genome bisulfite sequencing (WGBS) data from Arabidopsis thaliana and reduced representation bisulfite sequencing (RRBS) data from baboons), we show that our method provides well-calibrated test statistics in the presence of population structure. Further, it improves power to detect differentially methylated sites: in the RRBS data set, MACAU detected 1.6-fold more age-associated CpG sites than a beta-binomial model (the next best approach). Changes in these sites are consistent with known age-related shifts in DNA methylation levels, and are enriched near genes that are differentially expressed with age in the same population. Taken together, our results indicate that MACAU is an efficient, effective tool for analyzing bisulfite sequencing data, with particular salience to analyses of structured populations. MACAU is freely available at www.xzlab.org/software.html.
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