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首页> 外文期刊>BMC Genomics >Detection of differentially methylated regions from bisulfite-seq data by hidden Markov models incorporating genome-wide methylation level distributions
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Detection of differentially methylated regions from bisulfite-seq data by hidden Markov models incorporating genome-wide methylation level distributions

机译：通过包含全基因组甲基化水平分布的隐马尔可夫模型，从亚硫酸氢盐序列数据中检测差异甲基化区域

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Background Detection of differential methylation between biological samples is an important task in bisulfite-seq data analysis. Several studies have attempted de novo finding of differentially methylated regions (DMRs) using hidden Markov models (HMMs). However, there is room for improvement in the design of HMMs, especially on emission functions that evaluate the likelihood of differential methylation at each cytosine site. Results We describe a new HMM for DMR detection from bisulfite-seq data. Our method utilizes emission functions that combine binomial models for aligned read counts, and beta mixtures for incorporating genome-wide methylation level distributions. We also develop unsupervised learning algorithms to adjust parameters of the beta-binomial models depending on differential methylation types (up, down, and not changed). In experiments on both simulated and real datasets, the new HMM improves DMR detection accuracy compared with HMMs in our previous study. Furthermore, our method achieves better accuracy than other methods using Fisher's exact test and methylation level smoothing. Conclusions Our method enables accurate DMR detection from bisulfite-seq data. The implementation of our method is named ComMet, and distributed as a part of Bisulfighter package, which is available at http://epigenome.cbrc.jp/bisulfighter .
机译：背景生物样品之间甲基化差异的检测是亚硫酸氢盐序列数据分析中的重要任务。多项研究尝试使用隐马尔可夫模型（HMM）从头寻找差异甲基化区域（DMR）。但是，HMM的设计仍有改进的空间，尤其是在评估每个胞嘧啶位点差异甲基化可能性的发射功能上。结果我们描述了一种用于从亚硫酸氢盐序列数据进行DMR检测的新型HMM。我们的方法利用了发射函数，该函数结合了二项式模型以实现对齐的读数计数，并结合了β混合物来整合全基因组范围的甲基化水平分布。我们还开发了无监督的学习算法，以根据不同的甲基化类型（向上，向下和未更改）调整β-二项式模型的参数。在模拟数据集和真实数据集上的实验中，与我们之前的研究中的HMM相比，新的HMM提高了DMR检测的准确性。此外，与使用Fisher精确测试和甲基化水平平滑处理的其他方法相比，我们的方法具有更高的准确性。结论我们的方法能够从亚硫酸氢盐序列数据中准确检测DMR。我们的方法的实现名为ComMet，并作为Bisulfighter软件包的一部分分发，该软件包可从http://epigenome.cbrc.jp/bisulfighter获得。

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