A statistical framework for Illumina DNA methylation arrays
A statistical framework for Illumina DNA methylation arrays
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DOI：
10.1093/bioinformatics/btq553
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发表时间：
2010-11-01
期刊：
影响因子：
5.8
通讯作者：
Chu, Haitao
中科院分区：
文献类型：
--
作者：
Kuan, Pei Fen;Wang, Sijian;Chu, Haitao
动机：Illumina BeadArray 是一种流行的 DNA 甲基化分析平台，DNA 甲基化是与基因沉默和染色体不稳定相关的重要表观遗传事件。然而，当前的方法依赖于任意检测 P 值截止，将探针和样本从后续分析中排除作为质量控制步骤，这会导致观察缺失和信息丢失。我们希望有一种方法能够整合整个数据，但又考虑到各个观察结果的不同质量。结果：我们首先基于几个阳性对照样本研究并提出了一个统计框架，用于消除 Illumina 甲基化 BeadArray 中的偏差来源。然后，我们为 Illumina BeadArray 引入了一种名为 LumiWCluster 的基于加权模型的聚类，它根据检测 P 值系统地对每个观察值进行加权，并避免丢弃数据子集。 LumiWCluster 允许发现不同的甲基化模式并自动选择信息丰富的 CpG 位点。我们在两个公开的 Illumina GoldenGate 甲基化数据集（卵巢癌和肝细胞癌）上展示了 LumiWCluster 的优势。
Motivation: The Illumina BeadArray is a popular platform for profiling DNA methylation, an important epigenetic event associated with gene silencing and chromosomal instability. However, current approaches rely on an arbitrary detection P-value cutoff for excluding probes and samples from subsequent analysis as a quality control step, which results in missing observations and information loss. It is desirable to have an approach that incorporates the whole data, but accounts for the different quality of individual observations.Results: We first investigate and propose a statistical framework for removing the source of biases in Illumina Methylation BeadArray based on several positive control samples. We then introduce a weighted model-based clustering called LumiWCluster for Illumina BeadArray that weights each observation according to the detection P-values systematically and avoids discarding subsets of the data. LumiWCluster allows for discovery of distinct methylation patterns and automatic selection of informative CpG loci. We demonstrate the advantages of LumiWCluster on two publicly available Illumina GoldenGate Methylation datasets (ovarian cancer and hepatocellular carcinoma).