Newman Scott
Biostatistics & Bioinformatics Shared Resource, Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA.
Bioinformatics. 2015 Sep 1;31(17):2874-6. doi: 10.1093/bioinformatics/btv298. Epub 2015 May 7.
Copy number abnormalities (CNAs) such as somatically-acquired chromosomal deletions and duplications drive the development of cancer. As individual tumor genomes can contain tens or even hundreds of large and/or focal CNAs, a major difficulty is differentiating between important, recurrent pathogenic changes and benign changes unrelated to the subject's phenotype. Here we present Copy Number Explorer, an interactive tool for mining large copy number datasets. Copy Number Explorer facilitates rapid visual and statistical identification of recurrent regions of gain or loss, identifies the genes most likely to drive CNA formation using the cghMCR method and identifies recurrently broken genes that may be disrupted or fused. The software also allows users to identify recurrent CNA regions that may be associated with differential survival.
Copy Number Explorer is available under the GNU public license (GPL-3). Source code is available at: https://sourceforge.net/projects/copynumberexplorer/
拷贝数异常（CNA），如体细胞获得性染色体缺失和重复，驱动癌症的发展。由于单个肿瘤基因组可能包含数十甚至数百个大的和/或局灶性CNA，一个主要困难是区分重要的、复发性致病变化和与受试者表型无关的良性变化。在此，我们展示了拷贝数浏览器（Copy Number Explorer），这是一种用于挖掘大型拷贝数数据集的交互式工具。拷贝数浏览器有助于快速直观和统计识别增益或缺失的复发性区域，使用cghMCR方法识别最有可能驱动CNA形成的基因，并识别可能被破坏或融合的反复断裂基因。该软件还允许用户识别可能与差异生存相关的复发性CNA区域。
拷贝数浏览器根据GNU公共许可证（GPL - 3）提供。源代码可在以下网址获取：https://sourceforge.net/projects/copynumberexplorer/
