Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data

BMC Bioinformatics

Jianing Gao¹  Qinghua Shi¹  Yuanwei Zhang¹  Asim Ali¹  Xiaohua Jiang¹  Changlin Wan¹  Rongjun Ban¹  Huan Zhang¹  Zhenghua Yu²  Ao Li²  Qiguang Zang² 

[1] Molecular and Cell Genetics Laboratory, The CAS Key Laboratory of Innate Immunity and Chronic Diseases, Hefei National Laboratory for Physical Sciences at Microscale, School of Life Sciences, CAS Center for Excellence in Molecular Cell Science, University of Science and Technology of China;School of Information Science and Technology, University of Science and Technology of China;

关键词: Copy number variation;    Exome sequencing;    Functional analysis;    Cancer;   

DOI  :  10.1186/s12859-017-1833-3

来源: DOAJ

【 摘 要 】

Abstract Background Copy number variations (CNVs) are the main genetic structural variations in cancer genome. Detecting CNVs in genetic exome region is efficient and cost-effective in identifying cancer associated genes. Many tools had been developed accordingly and yet these tools lack of reliability because of high false negative rate, which is intrinsically caused by genome exonic bias. Results To provide an alternative option, here, we report Anaconda, a comprehensive pipeline that allows flexible integration of multiple CNV-calling methods and systematic annotation of CNVs in analyzing WES data. Just by one command, Anaconda can generate CNV detection result by up to four CNV detecting tools. Associated with comprehensive annotation analysis of genes involved in shared CNV regions, Anaconda is able to deliver a more reliable and useful report in assistance with CNV-associate cancer researches. Conclusion Anaconda package and manual can be freely accessed at http://mcg.ustc.edu.cn/bsc/ANACONDA/ .

【 授权许可】

Unknown