Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, United States.
Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States.
Bioinformatics. 2024 Aug 2;40(8). doi: 10.1093/bioinformatics/btae453.
Copy number variation (CNV) and alteration (CNA) analysis is a crucial component in many genomic studies and its applications span from basic research to clinic diagnostics and personalized medicine. CNVpytor is a tool featuring a read depth-based caller and combined read depth and B-allele frequency (BAF) based 2D caller to find CNVs and CNAs. The tool stores processed intermediate data and CNV/CNA calls in a compact HDF5 file-pytor file. Here, we describe a new track in igv.js that utilizes pytor and whole genome variant files as input for on-the-fly read depth and BAF visualization, CNV/CNA calling and analysis. Embedding into HTML pages and Jupiter Notebooks enables convenient remote data access and visualization simplifying interpretation and analysis of omics data.
The CNVpytor track is integrated with igv.js and available at https://github.com/igvteam/igv.js. The documentation is available at https://github.com/igvteam/igv.js/wiki/cnvpytor. Usage can be tested in the IGV-Web app at https://igv.org/app and also on https://github.com/abyzovlab/CNVpytor.
拷贝数变异（CNV）和改变（CNA）分析是许多基因组研究中的一个关键组成部分，其应用范围从基础研究到临床诊断和个性化医疗。CNVpytor 是一种工具，具有基于读取深度的调用器和结合读取深度和 B-等位基因频率（BAF）的 2D 调用器，用于发现 CNV 和 CNA。该工具将处理后的中间数据和 CNV/CNA 调用存储在紧凑的 HDF5 文件-pytor 文件中。在这里，我们描述了 igv.js 中的一个新跟踪，该跟踪利用 pytor 和全基因组变异文件作为输入，用于实时读取深度和 BAF 可视化、CNV/CNA 调用和分析。嵌入 HTML 页面和 Jupiter 笔记本可方便地进行远程数据访问和可视化，简化了对组学数据的解释和分析。
CNVpytor 跟踪与 igv.js 集成，并可在 https://github.com/igvteam/igv.js 上获得。文档可在 https://github.com/igvteam/igv.js/wiki/cnvpytor 上获得。可在 https://igv.org/app 的 IGV-Web 应用程序中测试用法，也可在 https://github.com/abyzovlab/CNVpytor 上测试。
