Suppr超能文献

CAPTVRED:一种用于从基于捕获的宏基因组学样本中进行病毒追踪和发现的自动化流程。

CAPTVRED: an automated pipeline for viral tracking and discovery from capture-based metagenomics samples.

作者信息

Tarradas-Alemany Maria, Martínez-Puchol Sandra, Mejías-Molina Cristina, Itarte Marta, Rusiñol Marta, Bofill-Mas Sílvia, Abril Josep F

机构信息

Computational Genomics Lab, Department of Genetics, Microbiology and Statistics, Universitat de Barcelona (UB), Institut de Biomedicina UB (IBUB), Barcelona, Catalonia 08028, Spain.

Laboratory of Viruses Contaminants of Water and Food, Department of Genetics, Microbiology and Statistics, Universitat de Barcelona (UB), Barcelona, Catalonia 08028, Spain.

出版信息

Bioinform Adv. 2024 Oct 8;4(1):vbae150. doi: 10.1093/bioadv/vbae150. eCollection 2024.

Abstract

SUMMARY

Target Enrichment Sequencing or Capture-based metagenomics has emerged as an approach of interest for viral metagenomics in complex samples. However, these datasets are usually analyzed with standard downstream Bioinformatics analyses. CAPTVRED (), has been designed to assess the virome present in complex samples, specially focused on those obtained by Target Enrichment Sequencing approach. This work aims to provide a user-friendly tool that complements this sequencing approach for the total or partial virome description, especially from environmental matrices. It includes a setup module which allows preparation and adjustment of the pipeline to any capture panel directed to a set of species of interest. The tool also aims to reduce time and computational cost, as well as to provide comprehensive, reproducible, and accessible results while being easy to costume, set up, and install.

AVAILABILITY AND IMPLEMENTATION

Source code and test datasets are freely available at github repository: https://github.com/CompGenLabUB/CAPTVRED.git.

摘要

摘要

靶向富集测序或基于捕获的宏基因组学已成为复杂样本中病毒宏基因组学一种备受关注的方法。然而,这些数据集通常采用标准的下游生物信息学分析方法进行分析。CAPTVRED()旨在评估复杂样本中存在的病毒组,特别关注通过靶向富集测序方法获得的样本。这项工作旨在提供一种用户友好的工具,以补充这种测序方法用于全面或部分病毒组描述,特别是来自环境基质的样本。它包括一个设置模块,可用于准备和调整流程以适应针对一组感兴趣物种的任何捕获面板。该工具还旨在减少时间和计算成本,并在易于定制、设置和安装的同时提供全面、可重复且可获取的结果。

可用性和实现方式

源代码和测试数据集可在github仓库免费获取:https://github.com/CompGenLabUB/CAPTVRED.git。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5eeb/11495672/61e2822f9667/vbae150f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验