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TB-Lineage:一种用于结核分枝杆菌复合群菌株分类和分析的在线工具。

TB-Lineage: an online tool for classification and analysis of strains of Mycobacterium tuberculosis complex.

机构信息

Computer Science Dept., Rensselaer Polytechnic Institute, Troy, NY, USA.

出版信息

Infect Genet Evol. 2012 Jun;12(4):789-97. doi: 10.1016/j.meegid.2012.02.010. Epub 2012 Mar 3.

Abstract

This paper formulates a set of rules to classify genotypes of the Mycobacterium tuberculosis complex (MTBC) into major lineages using spoligotypes and MIRU-VNTR results. The rules synthesize prior literature that characterizes lineages by spacer deletions and variations in the number of repeats seen at locus MIRU24 (alias VNTR2687). A tool that efficiently and accurately implements this rule base is now freely available at http://tbinsight.cs.rpi.edu/run_tb_lineage.html. When MIRU24 data is not available, the system utilizes predictions made by a Naïve Bayes classifier based on spoligotype data. This website also provides a tool to generate spoligoforests in order to visualize the genetic diversity and relatedness of genotypes and their associated lineages. A detailed analysis of the application of these tools on a dataset collected by the CDC consisting of 3198 distinct spoligotypes and 5430 distinct MIRU-VNTR types from 37,066 clinical isolates is presented. The tools were also tested on four other independent datasets. The accuracy of automated classification using both spoligotypes and MIRU24 is >99%, and using spoligotypes alone is >95%. This online rule-based classification technique in conjunction with genotype visualization provides a practical tool that supports surveillance of TB transmission trends and molecular epidemiological studies.

摘要

本文提出了一套利用 spoligotype 和 MIRU-VNTR 结果对结核分枝杆菌复合群(MTBC)基因型进行主要谱系分类的规则。这些规则综合了先前的文献,这些文献通过间隔缺失和 MIRU24 (别名 VNTR2687)位点重复数的变化来描述谱系。一个能够高效、准确地实现这一规则基础的工具现在可以在 http://tbinsight.cs.rpi.edu/run_tb_lineage.html 上免费获得。当 MIRU24 数据不可用时,系统会利用基于 spoligotype 数据的朴素贝叶斯分类器进行预测。该网站还提供了一个生成 spoligoforests 的工具,以便可视化基因型及其相关谱系的遗传多样性和相关性。本文详细分析了这些工具在由 CDC 收集的一个数据集上的应用,该数据集包含了来自 37066 个临床分离株的 3198 个独特 spoligotypes 和 5430 个独特 MIRU-VNTR 类型。这些工具还在另外四个独立的数据集上进行了测试。基于 spoligotypes 和 MIRU24 的自动分类的准确性>99%,仅基于 spoligotypes 的准确性>95%。这种在线基于规则的分类技术结合基因型可视化,提供了一种实用的工具,支持对结核病传播趋势和分子流行病学研究的监测。

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