Method to detect differentially methylated loci with case-control designs using Illumina arrays.
Method to detect differentially methylated loci with case-control designs using Illumina arrays.
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DOI：
10.1002/gepi.20619
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发表时间：
2011-11
影响因子：
2.1
通讯作者：
Wang, Shuang
中科院分区：
文献类型：
--
作者：
Wang, Shuang
现在已经知道，几乎所有的人类癌症类型都是遗传和表观遗传变化积累的结果。DNA甲基化是DNA的分子修饰，对正常发育至关重要。富含CpG二核苷酸的基因在正常组织中通常不甲基化，但在癌症中经常高甲基化。随着高通量平台的出现，通过全基因组扫描可以获得基因组甲基化模式的大规模结构，并且最近已经产生了大量的DNA甲基化数据。然而，复杂的统计方法来处理复杂的DNA甲基化数据是非常有限的。在这里，我们开发了一个基于似然的均匀正态混合模型，使用Illumina阵列选择病例组和对照组之间的差异甲基化位点。我们的想法是将数据建模为三种类型的甲基化位点，一种是未甲基化的，一种是完全甲基化的，一种是部分甲基化的。采用两个均匀分布和一个截尾正态分布的三组分混合模型对这三种类型进行建模。利用混合概率和正态分布的平均值对差异甲基化位点进行推断。通过大量的仿真研究，我们证明了所提出的方法的可行性和权力。最近发表的一项关于卵巢癌的研究的应用程序确定了现有方法遗漏的几个甲基化位点。
It is now understood that virtually all human cancer types are the result of the accumulation of both genetic and epigenetic changes. DNA methylation is a molecular modification of DNA that is crucial for normal development. Genes that are rich in CpG dinucleotides are usually not methylated in normal tissues, but are frequently hypermethylated in cancer. With the advent of high-throughput platforms, large-scale structure of genomic methylation patterns is available through genome-wide scans and tremendous amount of DNA methylation data have been recently generated. However, sophisticated statistical methods to handle complex DNA methylation data are very limited. Here we developed a likelihood based Uniform-Normal-mixture model to select differentially methylated loci between case and control groups using Illumina arrays. The idea is to model the data as three types of methylation loci, one unmethylated, one completely methylated, and one partially methylated. A three-component mixture model with two Uniform distributions and one truncated normal distribution was used to model the three types. The mixture probabilities and the mean of the normal distribution were used to make inference about differentially methylated loci. Through extensive simulation studies, we demonstrated the feasibility and power of the proposed method. An application to a recently published study on ovarian cancer identified several methylation loci that are missed by the existing method.
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影响因子：
--
作者：
Kalari, Satish;Pfeifer, Gerd P.
通讯作者：
Pfeifer, Gerd P.
影响因子：
4.5
作者：
Kerkel K;Schupf N;Hatta K;Pang D;Salas M;Kratz A;Minden M;Murty V;Zigman WB;Mayeux RP;Jenkins EC;Torkamani A;Schork NJ;Silverman W;Croy BA;Tycko B
通讯作者：
Tycko B
影响因子：
5.8
作者：
Kuan, Pei Fen;Wang, Sijian;Chu, Haitao
通讯作者：
Chu, Haitao
DOI：
10.1111/j.2517-6161.1977.tb01600.x
发表时间：
1977-01-01
期刊：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL
影响因子：
--
作者：
DEMPSTER, AP;LAIRD, NM;RUBIN, DB
通讯作者：
RUBIN, DB
影响因子：
13.5
作者：
Chung, Kit-Ying;Cheng, Ibis K-C;Wong, Nathalie
通讯作者：
Wong, Nathalie