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CONSTAX2:改进环境 DNA 标记物的分类学分类。

CONSTAX2: improved taxonomic classification of environmental DNA markers.

机构信息

Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA.

Department of Plant Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA.

出版信息

Bioinformatics. 2021 Nov 5;37(21):3941-3943. doi: 10.1093/bioinformatics/btab347.

Abstract

SUMMARY

CONSTAX-the CONSensus TAXonomy classifier-was developed for accurate and reproducible taxonomic annotation of fungal rDNA amplicon sequences and is based upon a consensus approach of RDP, SINTAX and UTAX algorithms. CONSTAX2 extends these features to classify prokaryotes as well as eukaryotes and incorporates BLAST-based classifiers to reduce classification errors. Additionally, CONSTAX2 implements a conda-installable command-line tool with improved classification metrics, faster training, multithreading support, capacity to incorporate external taxonomic databases and new isolate matching and high-level taxonomy tools, replete with documentation and example tutorials.

AVAILABILITY AND IMPLEMENTATION

CONSTAX2 is available at https://github.com/liberjul/CONSTAXv2, and is packaged for Linux and MacOS from Bioconda with use under the MIT License. A tutorial and documentation are available at https://constax.readthedocs.io/en/latest/. Data and scripts associated with the manuscript are available at https://github.com/liberjul/CONSTAXv2_ms_code.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

摘要

CONS-TAX(共识分类法)是一种真菌 rDNA 扩增子序列分类器,它基于 RDP、SINTAX 和 UTAX 算法的共识方法,旨在进行准确且可重复的分类注释。CON-STAX2 扩展了这些功能,可用于分类原核生物和真核生物,并结合了基于 BLAST 的分类器以减少分类错误。此外,CON-STAX2 实现了一个可通过 conda 安装的命令行工具,具有改进的分类指标、更快的训练速度、多线程支持、能够整合外部分类数据库以及新的分离物匹配和高级分类学工具,同时提供了文档和示例教程。

可用性和实现

CON-STAX2 可在 https://github.com/liberjul/CONSTAXv2 上获取,并通过 Bioconda 为 Linux 和 MacOS 打包,根据 MIT 许可证使用。在 https://constax.readthedocs.io/zh_CN/latest/ 上提供了教程和文档。与手稿相关的数据和脚本可在 https://github.com/liberjul/CONSTAXv2_ms_code 上获取。

补充信息

补充数据可在生物信息学在线获取。

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