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

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 beca...

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Autores principales: Gao, Jianing, Wan, Changlin, Zhang, Huan, Li, Ao, Zang, Qiguang, Ban, Rongjun, Ali, Asim, Yu, Zhenghua, Shi, Qinghua, Jiang, Xiaohua, Zhang, Yuanwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5627484/
https://www.ncbi.nlm.nih.gov/pubmed/28974218
http://dx.doi.org/10.1186/s12859-017-1833-3
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author Gao, Jianing
Wan, Changlin
Zhang, Huan
Li, Ao
Zang, Qiguang
Ban, Rongjun
Ali, Asim
Yu, Zhenghua
Shi, Qinghua
Jiang, Xiaohua
Zhang, Yuanwei
author_facet Gao, Jianing
Wan, Changlin
Zhang, Huan
Li, Ao
Zang, Qiguang
Ban, Rongjun
Ali, Asim
Yu, Zhenghua
Shi, Qinghua
Jiang, Xiaohua
Zhang, Yuanwei
author_sort Gao, Jianing
collection PubMed
description 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/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-017-1833-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-56274842017-10-12 Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data Gao, Jianing Wan, Changlin Zhang, Huan Li, Ao Zang, Qiguang Ban, Rongjun Ali, Asim Yu, Zhenghua Shi, Qinghua Jiang, Xiaohua Zhang, Yuanwei BMC Bioinformatics Software 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/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-017-1833-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-10-03 /pmc/articles/PMC5627484/ /pubmed/28974218 http://dx.doi.org/10.1186/s12859-017-1833-3 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Gao, Jianing
Wan, Changlin
Zhang, Huan
Li, Ao
Zang, Qiguang
Ban, Rongjun
Ali, Asim
Yu, Zhenghua
Shi, Qinghua
Jiang, Xiaohua
Zhang, Yuanwei
Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data
title Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data
title_full Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data
title_fullStr Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data
title_full_unstemmed Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data
title_short Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data
title_sort anaconda: an automated pipeline for somatic copy number variation detection and annotation from tumor exome sequencing data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5627484/
https://www.ncbi.nlm.nih.gov/pubmed/28974218
http://dx.doi.org/10.1186/s12859-017-1833-3
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