A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data.
A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data.
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beta混合分位数归一化方法，用于校正Illumina Infinium 450 K DNA甲基化数据中的探针设计偏差。
DOI：
10.1093/bioinformatics/bts680
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发表时间：
2013-01-15
期刊：
影响因子：
--
通讯作者：
Beck S
中科院分区：
文献类型：
--
作者：
Teschendorff AE;Marabita F;Lechner M;Bartlett T;Tegner J;Gomez-Cabrero D;Beck S
动机：Illumina Infinium 450 k DNA甲基化珠芯片是表观基因组广泛关联研究(Ewas)的首选候选技术。然而，与这些珠状阵列相关的一个困难是，探针有两种不同的设计，其特点是DNA甲基化分布和动态范围大不相同，这可能会偏向下游分析。因此，一个关键的统计问题是如何最好地调整以适应两种不同的探头设计。结果：针对450k数据，我们提出了一种新的基于模型的数组内归一化策略，称为BMIQ(Beta Mixine Decomle Expanation)，用于调整类型2设计探针的Beta值，以研究类型1探针的统计分布特征。该策略包括应用三态β-混合模型将探针分配给甲基化状态，随后将概率转换为分位数，最后进行甲基化依赖的膨胀转换，以保持数据的单调性和连续性。我们在细胞系数据、新鲜的冷冻和石蜡包埋的肿瘤组织样本上验证了我们的方法，并证明了BMIQ比两种竞争的方法更有利。具体地说，我们证明了BMIQ提高了归一化过程的稳健性，减少了类型2探针值的技术变异和偏差，并成功地消除了由于类型2探针动态范围较低而导致的类型1浓缩偏差。BMIQ将作为任何使用Illumina Infinium450k平台的研究的前处理步骤。可用性：BMIQ可从http://code.google.com/p/bmiq/.免费获得补充信息：BioInformation Online上提供补充数据
Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs. Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform. Availability: BMIQ is freely available from http://code.google.com/p/bmiq/. Contact: a.teschendorff@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online
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影响因子：
4.4
作者：
Bibikova, Marina;Barnes, Bret;Shen, Richard
通讯作者：
Shen, Richard
影响因子：
3.8
作者：
Dedeurwaerder, Sarah;Defrance, Matthieu;Fuks, Francois
通讯作者：
Fuks, Francois
影响因子：
3.7
作者：
Sandoval, Juan;Heyn, Holger A.;Esteller, Manel
通讯作者：
Esteller, Manel
DOI：
10.1038/nrg3000
发表时间：
2011-07-12
期刊：
Nature reviews. Genetics
影响因子：
--
作者：
通讯作者：
--
影响因子：
3
作者：
Zhuang J;Widschwendter M;Teschendorff AE
通讯作者：
Teschendorff AE