Accurate and reliable high-throughput detection of copy number variation in the human genome
Accurate and reliable high-throughput detection of copy number variation in the human genome
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DOI：
10.1101/gr.5630906
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发表时间：
2006-12-01
期刊：
影响因子：
7
通讯作者：
Carter, Nigel P.
中科院分区：
文献类型：
--
作者：
Fiegler, Heike;Redon, Richard;Carter, Nigel P.
这项研究描述了一种新的工具，用于准确和可靠的高通量检测人类基因组中的拷贝数变异。我们已经构建了一个大插入克隆DNA微阵列，覆盖了整个人类基因组的平铺路径分辨率，我们已经用来确定人类群体中的拷贝数变异。这项研究的关键是开发一个强大的阵列平台和分析过程，用于自动识别拷贝数变异（CNV）。该阵列由26，574个克隆组成，覆盖了93.7%的常染色质区域。克隆主要从已发表的“黄金路径”中选择，并通过指纹图谱和BAC末端测序确认定位。阵列性能通过一系列验证试验进行了广泛测试。这些包括通过染色体特异性添加实验确定阵列上每个单独克隆的杂交特征。使用自体-自体杂交、重复实验和CNVs的独立验证进行数据再现性和假阳性/阴性率的估计。基于这些研究，我们开发了一种基于方差的自动拷贝数检测分析过程（CNVfinder），并通过与SW-ARRAY方法的比较证明了其稳健性。
This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published "Golden Path," and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self-self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method.