Statistical method evaluation for differentially methylated CpGs in base resolution next-generation DNA sequencing data
Statistical method evaluation for differentially methylated CpGs in base resolution next-generation DNA sequencing data
复制标题
碱基分辨率下一代 DNA 测序数据中差异甲基化 CpG 的统计方法评估
DOI：
10.1093/bib/bbw133
复制
发表时间：
2016
影响因子：
9.5
通讯作者：
Zhifu Sun
中科院分区：
文献类型：
--
作者：
Yun Zhang;S. Baheti;Zhifu Sun
高通量亚硫酸氢甲基化测序通常用于碱基拆分甲基组研究，如简化代表性亚硫酸氢盐测序(RRBS)、Agilent SureSelect Human Methyl-Seq(甲基-SEQ)或全基因组亚硫酸盐甲基化测序法。这些数据要么用CpG位点的甲基化胞嘧啶与总覆盖率的比率表示，要么用甲基化和非甲基化胞嘧啶的数量来表示。多种统计方法可以用来检测不同条件之间的差异甲基化CPCs，这些方法通常是下一步差异甲基化区域识别的基础。比率数据可以灵活地适用于许多线性模型，但原始计数数据考虑了覆盖信息。每种数据类型中都有一系列用于DMC检测的选项；但是，尚不清楚哪种是最佳的统计方法。在这项研究中，我们系统地评估了四种甲基化比率统计方法和四种基于计数的数据统计方法，并利用真实的RRBS数据结合模拟比较了它们在第一类错误控制、DMC检测的灵敏度和特异度以及计算资源需求方面的性能。我们的结果表明，基于比率的测试通常比基于计数的测试更保守(不那么敏感)。然而，一些基于计数的方法有很高的假阳性率，应该避免。贝塔二项模型在敏感性和特异性之间取得了很好的平衡，是首选的方法。文中还讨论了在不同环境下的方法选择、信噪比和样本量估计。
High-throughput bisulfite methylation sequencing such as reduced representation bisulfite sequencing (RRBS), Agilent SureSelect Human Methyl-Seq (Methyl-seq) or whole-genome bisulfite sequencing is commonly used for base resolution methylome research. These data are represented either by the ratio of methylated cytosine versus total coverage at a CpG site or numbers of methylated and unmethylated cytosines. Multiple statistical methods can be used to detect differentially methylated CpGs (DMCs) between conditions, and these methods are often the base for the next step of differentially methylated region identification. The ratio data have a flexibility of fitting to many linear models, but the raw count data take consideration of coverage information. There is an array of options in each datatype for DMC detection; however, it is not clear which is an optimal statistical method. In this study, we systematically evaluated four statistic methods on methylation ratio data and four methods on count-based data and compared their performances with regard to type I error control, sensitivity and specificity of DMC detection and computational resource demands using real RRBS data along with simulation. Our results show that the ratio-based tests are generally more conservative (less sensitive) than the count-based tests. However, some count-based methods have high false-positive rates and should be avoided. The beta-binomial model gives a good balance between sensitivity and specificity and is preferred method. Selection of methods in different settings, signal versus noise and sample size estimation are also discussed.
影响因子：
15.9
作者：
Meldi, Kristen;Qin, Tingting;Figueroa, Maria E.
通讯作者：
Figueroa, Maria E.