ArticleBioinformatics (Oxford, England)2016
LuxGLM: a probabilistic covariate model for quantification of DNA methylation modifications with complex experimental designs.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 24 citations in OpenAlex.
- LuxHMM: DNA methylation analysis with genome segmentation via hidden Markov model.BMC bioinformatics · 2023Article
- A comprehensive approach for genome-wide efficiency profiling of DNA modifying enzymes.Cell reports methods · 2022Article
- LuxRep: a technical replicate-aware method for bisulfite sequencing data analysis.BMC bioinformatics · 2022Article
- LuxUS: DNA methylation analysis using generalized linear mixed model with spatial correlation.Bioinformatics (Oxford, England) · 2020Article
- TET enzymes augment activation-induced deaminase (AID) expression via 5-hydroxymethylcytosine modifications at theScience immunology · 2019Article
- TET Methylcytosine Oxidases in T Cell and B Cell Development and Function.Frontiers in immunology · 2017Review
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Authors and funding
4 authors at 4 institutions in 2 countries.
Funding
Abstract
motivation5-methylcytosine (5mC) is a widely studied epigenetic modification of DNA. The ten-eleven translocation (TET) dioxygenases oxidize 5mC into oxidized methylcytosines (oxi-mCs): 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC). DNA methylation modifications have multiple functions. For example, 5mC is shown to be associated with diseases and oxi-mC species are reported to have a role in active DNA demethylation through 5mC oxidation and DNA repair, among others, but the detailed mechanisms are poorly understood. Bisulphite sequencing and its various derivatives can be used to gain information about all methylation modifications at single nucleotide resolution. Analysis of bisulphite based sequencing data is complicated due to the convoluted read-outs and experiment-specific variation in biochemistry. Moreover, statistical analysis is often complicated by various confounding effects. How to analyse 5mC and oxi-mC data sets with arbitrary and complex experimental designs is an open and important problem.
resultsWe propose the first method to quantify oxi-mC species with arbitrary covariate structures from bisulphite based sequencing data. Our probabilistic modeling framework combines a previously proposed hierarchical generative model for oxi-mC-seq data and a general linear model component to account for confounding effects. We show that our method provides accurate methylation level estimates and accurate detection of differential methylation when compared with existing methods. Analysis of novel and published data gave insights into to the demethylation of the forkhead box P3 (Foxp3) locus during the induced T regulatory cell differentiation. We also demonstrate how our covariate model accurately predicts methylation levels of the Foxp3 locus. Collectively, LuxGLM method improves the analysis of DNA methylation modifications, particularly for oxi-mC species. AVAILABILITY AND IMPLEMENTATION: An implementation of the proposed method is available under MIT license at https://github.org/tare/LuxGLM/ CONTACT: taijo@simonsfoundation.org or harri.lahdesmaki@aalto.fi SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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