Nancarrow Derek J, Handoko Herlina Y, Stark Mitchell S, Whiteman David C, Hayward Nicholas K
Oncogenomics, Queensland Institute of Medical Research, Herston, Queensland, Australia.
PLoS One. 2007 Oct 31;2(10):e1093. doi: 10.1371/journal.pone.0001093.
The recent application of genome-wide, single nucleotide polymorphism (SNP) microarrays to investigate DNA copy number aberrations in cancer has provided unparalleled sensitivity for identifying genomic changes. In some instances the complexity of these changes makes them difficult to interpret, particularly when tumour samples are contaminated with normal (stromal) tissue. Current automated scoring algorithms require considerable manual data checking and correction, especially when assessing uncultured tumour specimens. To address these limitations we have developed a visual tool to aid in the analysis of DNA copy number data. Simulated DNA Copy Number (SiDCoN) is a spreadsheet-based application designed to simulate the appearance of B-allele and logR plots for all known types of tumour DNA copy number changes, in the presence or absence of stromal contamination. The system allows the user to determine the level of stromal contamination, as well as specify up to 3 different DNA copy number aberrations for up to 5000 data points (representing individual SNPs). This allows users great flexibility to assess simple or complex DNA copy number combinations. We demonstrate how this utility can be used to estimate the level of stromal contamination within tumour samples and its application in deciphering the complex heterogeneous copy number changes we have observed in a series of tumours. We believe this tool will prove useful to others working in the area, both as a training tool, and to aid in the interpretation of complex copy number changes.
近期,全基因组单核苷酸多态性(SNP)微阵列技术在癌症DNA拷贝数畸变研究中的应用,为识别基因组变化提供了无与伦比的灵敏度。在某些情况下,这些变化的复杂性使得它们难以解释,尤其是当肿瘤样本被正常(基质)组织污染时。当前的自动评分算法需要大量的人工数据检查和校正,特别是在评估未经培养的肿瘤标本时。为了解决这些局限性,我们开发了一种可视化工具来辅助DNA拷贝数数据分析。模拟DNA拷贝数(SiDCoN)是一个基于电子表格的应用程序,旨在模拟在存在或不存在基质污染的情况下,所有已知类型肿瘤DNA拷贝数变化的B等位基因和logR图的外观。该系统允许用户确定基质污染水平,并为多达5000个数据点(代表单个SNP)指定多达3种不同的DNA拷贝数畸变。这使得用户在评估简单或复杂的DNA拷贝数组合时具有很大的灵活性。我们展示了如何使用该实用程序来估计肿瘤样本中的基质污染水平,以及它在解读我们在一系列肿瘤中观察到的复杂异质性拷贝数变化中的应用。我们相信这个工具对该领域的其他研究人员将是有用的,既可以作为一种培训工具,也有助于解释复杂的拷贝数变化。