A statistical change point model approach for the detection of DNA copy number variations in array CGH data.
A statistical change point model approach for the detection of DNA copy number variations in array CGH data.
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DOI：
10.1109/tcbb.2008.129
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发表时间：
2009-10
期刊：
影响因子：
--
通讯作者：
Wang YP
中科院分区：
文献类型：
--
作者：
Chen J;Wang YP
阵列比较基因组杂交（aCGH）提供了一种高分辨率和高通量的技术，用于筛选整个基因组内的拷贝数变异（CNVs）。与常规CGH相比，该技术显著提高了染色体异常的鉴定。然而，由于成像和杂交过程中遗传的随机噪声，在aCGH数据中识别统计学显著的DNA拷贝数变化是具有挑战性的。我们提出了一种新的方法，使用均值和方差变点模型（MVCM）检测CNVs或断点在aCGH数据集。我们推导出检验统计量的近似p值，并给出了DNA拷贝数变化位点的估计。我们进行模拟研究，以评估估计的准确性和p值制定。这些模拟结果表明，该方法是有效的，在识别拷贝数的变化。该方法还在公开可用的成纤维细胞癌细胞系数据、乳腺肿瘤细胞系数据和乳腺癌细胞系aCGH数据集上进行了测试。我们的方法在这些细胞系上检测到未通过环形二进制分割（CBS）方法鉴定但经过生物学验证的变化，其灵敏度和特异性高于CBS。
Array comparative genomic hybridization (aCGH) provides a high-resolution and high-throughput technique for screening of copy number variations (CNVs) within the entire genome. This technique, compared to the conventional CGH, significantly improves the identification of chromosomal abnormalities. However, due to the random noise inherited in the imaging and hybridization process, identifying statistically significant DNA copy number changes in aCGH data is challenging. We propose a novel approach that uses the mean and variance change point model (MVCM) to detect CNVs or breakpoints in aCGH data sets. We derive an approximate p-value for the test statistic and also give the estimate of the locus of the DNA copy number change. We carry out simulation studies to evaluate the accuracy of the estimate and the p-value formulation. These simulation results show that the approach is effective in identifying copy number changes. The approach is also tested on fibroblast cancer cell line data, breast tumor cell line data, and breast cancer cell line aCGH data sets that are publicly available. Changes that have not been identified by the circular binary segmentation (CBS) method but are biologically verified are detected by our approach on these cell lines with higher sensitivity and specificity than CBS.