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首页> 外文期刊>BMC Bioinformatics >Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
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Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis

机译:通过微阵列分析定量甲基化水平的Beta值和M值方法的比较

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Background High-throughput profiling of DNA methylation status of CpG islands is crucial to understand the epigenetic regulation of genes. The microarray-based Infinium methylation assay by Illumina is one platform for low-cost high-throughput methylation profiling. Both Beta-value and M-value statistics have been used as metrics to measure methylation levels. However, there are no detailed studies of their relations and their strengths and limitations. Results We demonstrate that the relationship between the Beta-value and M-value methods is a Logit transformation, and show that the Beta-value method has severe heteroscedasticity for highly methylated or unmethylated CpG sites. In order to evaluate the performance of the Beta-value and M-value methods for identifying differentially methylated CpG sites, we designed a methylation titration experiment. The evaluation results show that the M-value method provides much better performance in terms of Detection Rate (DR) and True Positive Rate (TPR) for both highly methylated and unmethylated CpG sites. Imposing a minimum threshold of difference can improve the performance of the M-value method but not the Beta-value method. We also provide guidance for how to select the threshold of methylation differences. Conclusions The Beta-value has a more intuitive biological interpretation, but the M-value is more statistically valid for the differential analysis of methylation levels. Therefore, we recommend using the M-value method for conducting differential methylation analysis and including the Beta-value statistics when reporting the results to investigators.
机译:背景技术高通量分析CpG岛的DNA甲基化状态对于了解基因的表观遗传调控至关重要。 Illumina基于微阵列的Infinium甲基化分析是低成本高通量甲基化分析的一个平台。 Beta值和M值统计信息均已用作衡量甲基化水平的指标。但是,没有关于它们之间的关系以及它们的优缺点的详细研究。结果我们证明Beta值方法和M值方法之间的关系是Logit变换,并且表明Beta值方法对于高度甲基化或未甲基化的CpG位点具有严重的异方差性。为了评估Beta值和M值方法识别差异甲基化CpG位点的性能,我们设计了一个甲基化滴定实验。评估结果表明,对于高度甲基化和未甲基化的CpG位点,M值方法在检测率(DR)和真实阳性率(TPR)方面提供了更好的性能。施加最小差异阈值可以提高M值方法的性能,但不能提高Beta值方法的性能。我们还提供有关如何选择甲基化差异阈值的指导。结论Beta值具有更直观的生物学解释,但M值在统计学上更有效地用于甲基化水平的差异分析。因此,我们建议在向研究人员报告结果时,使用M值方法进行差异甲基化分析,并包括Beta值统计信息。

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