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Reliability of DNA methylation measures using Illumina methylation BeadChip
Epigenetics ( IF 3.7 ) Pub Date : 2020-08-15 , DOI: 10.1080/15592294.2020.1805692
Zongli Xu 1 , Jack A Taylor 1, 2
Affiliation  

ABSTRACT

Illumina BeadChips are widely utilized in epigenome-wide association studies (EWAS). Several studies have reported that many probes on these arrays have poor reliability. Here, we compare different pre-processing methods to improve intra-class correlation coefficients (ICC). We describe the characteristics of ICC across the genome, within and between studies, and across different array platforms. Using technical duplicates from 128 subjects, we find that with raw data only 22.5% of the CpGs on 450 K array have ‘acceptable’ ICCs (>0.5). Data preprocessing steps, such as background correction and dye bias correction, can reduce technical noise and improve the percentage to 38.5%. Similar to previous studies, we found that ICC is associated with CpG methylation level such that 83% of CpGs with intermediate methylation (0.1< beta-value <0.9) have acceptable ICCs, whereas only 21% of CpGs with low or high methylation (beta-value <0.1 or >0.9) have acceptable ICCs. ICC is also correlated with CpG methylation variance; after mutual adjustment for beta-value and variance, only variance remains correlated. Many CpGs with poor ICCs (<0.5) are located in biologically important regulatory regions, including gene promoters and CpG islands. Poor ICC at these sites appears to be a consequence of low biologic variation among individuals rather than increased technical measurement variation. ICCs quality classifications are highly concordant across different array platforms and across different studies. We find that ICC can be reliably estimated with 30 pairs of duplicate samples. CpGs with acceptable ICC have higher study power and are more commonly reported in published epigenome-wide studies.



中文翻译:

使用 Illumina 甲基化 BeadChip 进行 DNA 甲基化测量的可靠性

摘要

Illumina BeadChip 芯片广泛用于表观基因组范围的关联研究 (EWAS)。几项研究报告说,这些阵列上的许多探针可靠性很差。在这里,我们比较了不同的预处理方法以提高类内相关系数 (ICC)。我们描述了 ICC 跨基因组、研究内部和研究之间以及不同阵列平台的特征。使用来自 128 个受试者的技术副本,我们发现使用原始数据,450 K 阵列上只有 22.5% 的 CpG 具有“可接受的”ICC(>0.5)。数据预处理步骤,如背景校正和染料偏差校正,可以减少技术噪声并将百分比提高到 38.5%。与之前的研究类似,我们发现 ICC 与 CpG 甲基化水平相关,因此 83% 的 CpG 具有中间甲基化(0.1< beta 值 <0. 9) 具有可接受的 ICC,而只有 21% 的低或高甲基化(β 值 <0.1 或 >0.9)的 CpG 具有可接受的 ICC。ICC 还与 CpG 甲基化方差相关;在对 beta 值和方差进行相互调整后,只有方差保持相关。许多 ICC 较差 (<0.5) 的 CpG 位于生物学上重要的调控区域,包括基因启动子和 CpG 岛。这些地点的 ICC 较差似乎是个体间生物学差异较低的结果,而不是技术测量差异增加的结果。ICC 质量分类在不同阵列平台和不同研究中高度一致。我们发现可以使用 30 对重复样本可靠地估计 ICC。

更新日期:2020-08-15
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