CNVpytor: a tool for copy number variation detection and analysis from read depth and allele imbalance in whole-genome sequencing.
CNVpytor: a tool for copy number variation detection and analysis from read depth and allele imbalance in whole-genome sequencing.
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DOI：
10.1093/gigascience/giab074
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发表时间：
2021-11-18
期刊：
影响因子：
9.2
通讯作者：
Abyzov A
中科院分区：
文献类型：
--
作者：
Suvakov M;Panda A;Diesh C;Holmes I;Abyzov A
基于全基因组测序数据检测拷贝数变异（CNV）和拷贝数改变（CNA）对于个性化基因组学和治疗非常重要。CNVnator是基于读取深度的CNV/CNA发现和分析的最流行的工具之一。在这里，我们提出了在Python中开发的CNVnator的扩展-CNVpytor。CNVpytor继承了其前身的重新实现的核心引擎，并扩展了可视化，模块化，性能和功能。此外，CNVpytor使用来自单核苷酸多态性和小插入缺失数据的B等位基因频率似然信息作为CNV/CNA的额外证据，并作为杂合性拷贝数中性丢失的主要信息。CNVpytor比CNVnator要快得多，特别是在解析对齐文件时（快2-20倍），而且中间文件更小（20-50倍）。CNV调用可以使用几个标准进行过滤，注释，并在多个样本上合并。模块化架构允许它在共享和云环境中使用，如Google Colab和Google Notebook。数据可以导出到JBrowse中，而用于JBrowse的CNVpytor的轻量级插件版本可以让任何用户几乎即时和GUI辅助分析CNV。CNVpytor版本和源代码可以在GitHub上获得，网址是https://github.com/abyzovlab/CNVpytor，使用MIT许可证。
Detecting copy number variations (CNVs) and copy number alterations (CNAs) based on whole-genome sequencing data is important for personalized genomics and treatment. CNVnator is one of the most popular tools for CNV/CNA discovery and analysis based on read depth. Herein, we present an extension of CNVnator developed in Python—CNVpytor. CNVpytor inherits the reimplemented core engine of its predecessor and extends visualization, modularization, performance, and functionality. Additionally, CNVpytor uses B-allele frequency likelihood information from single-nucleotide polymorphisms and small indels data as additional evidence for CNVs/CNAs and as primary information for copy number–neutral losses of heterozygosity. CNVpytor is significantly faster than CNVnator—particularly for parsing alignment files (2–20 times faster)—and has (20–50 times) smaller intermediate files. CNV calls can be filtered using several criteria, annotated, and merged over multiple samples. Modular architecture allows it to be used in shared and cloud environments such as Google Colab and Jupyter notebook. Data can be exported into JBrowse, while a lightweight plugin version of CNVpytor for JBrowse enables nearly instant and GUI-assisted analysis of CNVs by any user. CNVpytor release and the source code are available on GitHub at https://github.com/abyzovlab/CNVpytor under the MIT license.
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影响因子：
3.7
作者：
Legault MA;Girard S;Lemieux Perreault LP;Rouleau GA;Dubé MP
通讯作者：
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DOI：
10.1093/bioinformatics/btr670
发表时间：
2012-02-01
期刊：
Bioinformatics (Oxford, England)
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通讯作者：
Korbel JO
DOI：
10.1016/j.tube.2014.02.005
发表时间：
2014-05
期刊：
Tuberculosis (Edinburgh, Scotland)
影响因子：
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作者：
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影响因子：
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作者：
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