Supervised learning for the automated transcription of spacer classification from spoligotype films.
Supervised learning for the automated transcription of spacer classification from spoligotype films.
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DOI：
10.1186/1471-2105-10-248
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发表时间：
2009-08-12
影响因子：
3
通讯作者：
de Jong BC
中科院分区：
文献类型：
--
作者：
Jeffries DJ;Abernethy N;de Jong BC
细菌的分子基因分型彻底改变了结核病流行病学的研究，但这些已建立的实验室技术通常需要训练有素的专业人员进行主观和费力的解释。在冈比亚的结核病病例接触研究中，我们使用了称为 spoligotype 分析的反向杂交实验室测定。为了促进 spoligotype 图像的处理，我们开发了工具和算法，可以自动将这些数据分类并直接转录到数据库，同时允许手动编辑。使用两种监督学习算法对从 spoligo 电影上 1849 个点中提取的特征进行分类。图形用户界面允许在导出到数据库之前手动编辑分类。该应用程序在 10 部不同质量的胶片上进行了测试，并将最佳分类器的结果与专家手动分类进行了比较，得出中值正确分类率为 98.1%（四分位数范围：97.1% 至 99.2%），每部胶片的自动处理时间不到 1 分钟。该软件实现比手动处理节省了大量时间，同时允许专家编辑自动分类。将分类自动上传到数据库可以减少转录错误的可能性。
Molecular genotyping of bacteria has revolutionized the study of tuberculosis epidemiology, yet these established laboratory techniques typically require subjective and laborious interpretation by trained professionals. In the context of a Tuberculosis Case Contact study in The Gambia we used a reverse hybridization laboratory assay called spoligotype analysis. To facilitate processing of spoligotype images we have developed tools and algorithms to automate the classification and transcription of these data directly to a database while allowing for manual editing. Features extracted from each of the 1849 spots on a spoligo film were classified using two supervised learning algorithms. A graphical user interface allows manual editing of the classification, before export to a database. The application was tested on ten films of differing quality and the results of the best classifier were compared to expert manual classification, giving a median correct classification rate of 98.1% (inter quartile range: 97.1% to 99.2%), with an automated processing time of less than 1 minute per film. The software implementation offers considerable time savings over manual processing whilst allowing expert editing of the automated classification. The automatic upload of the classification to a database reduces the chances of transcription errors.
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