Detection of DNA copy number alterations using penalized least squares regression
Detection of DNA copy number alterations using penalized least squares regression
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DOI：
10.1093/bioinformatics/bti646
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发表时间：
2005-10-15
期刊：
影响因子：
5.8
通讯作者：
Zhao, HY
中科院分区：
文献类型：
--
作者：
Huang, T;Wu, BL;Zhao, HY
动机：基因组DNA拷贝数变异是包括癌症在内的许多人类疾病的特征。人们已经提出了各种技术和平台，使研究人员能够将整个基因组划分成连续片段之间拷贝数发生变化的片段，并随后对DNA拷贝数变异进行量化。在本文中，我们将DNA拷贝数数据的空间依赖性纳入回归模型，并将DNA拷贝数变异的检测形式化为一个惩罚最小二乘回归问题。此外，我们使用平稳自助法来估计统计显著性和错误发现率。
结果：通过模拟研究了所提出的方法，并通过对文献中一个经过广泛分析的数据集的应用进行了说明。结果表明，所提出的方法能够正确检测出真实断点的数量和位置，同时适当控制假阳性。
Motivation: Genomic DNA copy number alterations are characteristic of many human diseases including cancer. Various techniques and platforms have been proposed to allow researchers to partition the whole genome into segments where copy numbers change between contiguous segments, and subsequently to quantify DNA copy number alterations. In this paper, we incorporate the spatial dependence of DNA copy number data into a regression model and formalize the detection of DNA copy number alterations as a penalized least squares regression problem. In addition, we use a stationary bootstrap approach to estimate the statistical significance and false discovery rate.Results: The proposed method is studied by simulations and illustrated by an application to an extensively analyzed dataset in the literature. The results show that the proposed method can correctly detect the numbers and locations of the true breakpoints while appropriately controlling the false positives.