DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors.
DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors.
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Dinamic：一种识别肿瘤中复发性DNA拷贝数像差的方法。
DOI：
10.1093/bioinformatics/btq717
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发表时间：
2011-03-01
期刊：
影响因子：
--
通讯作者：
Wright FA
中科院分区：
文献类型：
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作者：
Walter V;Nobel AB;Wright FA
动机：DNA拷贝数的增加和丢失在肿瘤组织中很常见，其中一些异常在肿瘤的发生和发展中发挥了作用。虽然使用基于阵列的技术可以获得高分辨率的DNA拷贝数数据，但没有一种单一的方法被广泛用于区分复发性拷贝数偏差和零星拷贝数偏差。结果：我们介绍了发现癌症中表现出的拷贝数异常(DiNAMIC)，这是一种评估复发性拷贝数异常的统计学意义的新方法。与竞争程序不同，DiNAMIC的测试程序是精心设计的，并采用了一种新的循环置换方案。广泛的模拟研究表明，DiNAMIC控制着各种现实场景中的假阳性发现。我们使用DiNAMIC分析了两个公开可用的肿瘤数据集，我们的结果表明DiNAMIC检测到了多个具有生物学相关性的基因座。可用性：用R实现的源代码以及包含示例和样例数据集的文本文件可在http://www.bios.unc.edu/research/genomic_software/DiNAMIC.上获得联系人：vwalter@email.unc.edu；fwright@bios.unc.edu补充信息：补充数据可在BioInformation Online上获得。
Motivation: DNA copy number gains and losses are commonly found in tumor tissue, and some of these aberrations play a role in tumor genesis and development. Although high resolution DNA copy number data can be obtained using array-based techniques, no single method is widely used to distinguish between recurrent and sporadic copy number aberrations. Results: Here we introduce Discovering Copy Number Aberrations Manifested In Cancer (DiNAMIC), a novel method for assessing the statistical significance of recurrent copy number aberrations. In contrast to competing procedures, the testing procedure underlying DiNAMIC is carefully motivated, and employs a novel cyclic permutation scheme. Extensive simulation studies show that DiNAMIC controls false positive discoveries in a variety of realistic scenarios. We use DiNAMIC to analyze two publicly available tumor datasets, and our results show that DiNAMIC detects multiple loci that have biological relevance. Availability: Source code implemented in R, as well as text files containing examples and sample datasets are available at http://www.bios.unc.edu/research/genomic_software/DiNAMIC. Contact: vwalter@email.unc.edu; fwright@bios.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online.