COPS

Copy Number Alterations (CNAs) such as deletions and duplications; compose a larger percentage of genetic variations than single nucleotide polymorphisms or other structural variations in cancer genomes that undergo major chromosomal re-arrangements. It is, therefore, imperative to identify cancer-specific somatic copy number alterations (SCNAs), with respect to matched normal tissue, in order to understand their association with the disease. We have devised an accurate, sensitive, and easy-to-use tool, COPS, COpy number using Paired Samples, for detecting SCNAs. We rigorously tested the performance of COPS using short sequence simulated reads at various sizes and coverage of SCNAs, read depths, read lengths and also with real tumor:normal paired samples. We found COPS to perform better in comparison to other known SCNA detection tools for all evaluated parameters, namely, sensitivity (detection of true positives), specificity (detection of false positives) and size accuracy. COPS performed well for sequencing reads of all lengths when used with most upstream read alignment tools. Additionally, by incorporating a downstream boundary segmentation detection tool, the accuracy of SCNA boundaries was further improved. Here, we report an accurate, sensitive and easy to use tool in detecting cancer-specific SCNAs using short-read sequence data. In addition to cancer, COPS can be used for any disease as long as sequence reads from both disease and normal samples from the same individual are available. An added boundary segmentation detection module makes COPS detected SCNA boundaries more specific for the samples studied. COPS is available at ftp://115.119.160.213 with username “cops” and password “cops”.

拷贝数变异（Copy Number Alterations, CNAs，包括缺失与重复）在发生大规模染色体重排的癌症基因组中，所占遗传变异比例高于单核苷酸多态性（Single Nucleotide Polymorphisms, SNPs）或其他结构变异。因此，为阐明其与疾病的关联，针对匹配的正常组织鉴定癌症特异性体细胞拷贝数变异（Somatic Copy Number Alterations, SCNAs）至关重要。我们开发了一款精准、灵敏且易于使用的工具——COPS（基于配对样本的拷贝数分析工具，全称COpy number using Paired Samples），用于检测体细胞拷贝数变异。我们通过多种方式严格评估了COPS的性能：使用不同长度与覆盖度的体细胞拷贝数变异模拟短序列测序读段，调整测序深度与读长，并使用真实的肿瘤-正常配对样本进行验证。结果显示，在所有评估参数（即灵敏度（真阳性检出率）、特异性（假阳性检出率）与片段大小准确性）下，COPS的表现均优于其他已知的体细胞拷贝数变异检测工具。当搭配绝大多数主流上游读段比对工具使用时，COPS对所有长度的测序读段均表现优异。此外，通过整合下游边界分割检测模块，体细胞拷贝数变异边界的检测准确性得到进一步提升。本文报道了一款可基于短读段测序数据精准、灵敏且便捷地检测癌症特异性体细胞拷贝数变异的工具。除癌症研究外，只要能获取同一患者的疾病组织与正常组织的测序读段，COPS即可应用于任何疾病的相关研究。额外搭载的边界分割检测模块，可使COPS所检测的体细胞拷贝数变异边界针对研究样本更具特异性。COPS的下载地址为ftp://115.119.160.213，用户名为"cops"，密码为"cops"。