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

Jianing Gao,Qinghua Shi,Ao Li,Asim Ali,Changlin Wan,Qiguang Zang,Yuanwei Zhang,Huan Zhang,Xiaohua Jiang,Zhenghua Yu,Rongjun Ban

doi:10.1186/s12859-017-1833-3

Abstract

BackgroundCopy 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.ResultsTo 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.ConclusionAnaconda package and manual can be freely accessed at http://mcg.ustc.edu.cn/bsc/ANACONDA/.

Highlights

Copy number variations (CNVs) are the main genetic structural variations in cancer genome
We developed Anaconda (AN Automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data), which successfully satisfied the requirements: 1) Anaconda is designed to be compatible with ease of use and rich features
Tested on our in-house input, ExomeCNV performed slightly slower than EXCAVATOR and ADTEx but out-performed than Control-FREEC. 2) Precision: we identified the precision of each tool based on existing comparisons, especially focus on the comparison conducted on clinical data

Summary

Introduction

Copy number variations (CNVs) are the main genetic structural variations in cancer genome. We developed Anaconda (AN Automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data), which successfully satisfied the requirements: 1) Anaconda is designed to be compatible with ease of use and rich features. Anaconda will extract the detected CNV results of the user-selected methods.

Results

Conclusion