A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways

Research output: Contribution to journalArticle


Research units

  • Simons Center for Data Analysis
  • Texas A and M University
  • German Cancer Research Center
  • La Jolla Institute for Allergy and Immunology


We present a generative model, Lux, to quantify DNA methylation modifications from any combination of bisulfite sequencing approaches, including reduced, oxidative, TET-assisted, chemical-modification assisted, and methylase-assisted bisulfite sequencing data. Lux models all cytosine modifications (C, 5mC, 5hmC, 5fC, and 5caC) simultaneously together with experimental parameters, including bisulfite conversion and oxidation efficiencies, as well as various chemical labeling and protection steps. We show that Lux improves the quantification and comparison of cytosine modification levels and that Lux can process any oxidized methylcytosine sequencing data sets to quantify all cytosine modifications. Analysis of targeted data from Tet2-knockdown embryonic stem cells and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathways and reveals 5hmC localization in putative regulatory regions.


Original languageEnglish
Article number49
Pages (from-to)1-22
Issue number1
Publication statusPublished - 14 Mar 2016
MoE publication typeA1 Journal article-refereed

    Research areas

  • 5-methylcytosine oxidation, Bayesian analysis, Bisulfite sequencing, BS-seq/oxBS-seq/TAB-seq/fCAB-seq/CAB-seq/redBS-seq/MAB-seq, DNA methylation, Hierarchical modeling, TET proteins

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