Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo 108-8693, Japan.
Bioinformatics. 2021 Sep 29;37(18):3021-3022. doi: 10.1093/bioinformatics/btab101.
Microorganisms infect and contaminate eukaryotic cells during the course of biological experiments. Because microbes influence host cell biology and may therefore lead to erroneous conclusions, a computational platform that facilitates decontamination is indispensable. Recent studies show that next-generation sequencing (NGS) data can be used to identify the presence of exogenous microbial species. Previously, we proposed an algorithm to improve detection of microbes in NGS data. Here, we developed an online application, OpenContami, which allows researchers easy access to the algorithm via interactive web-based interfaces. We have designed the application by incorporating a database comprising analytical results from a large-scale public dataset and data uploaded by users. The database serves as a reference for assessing user data and provides a list of genera detected from negative blank controls as a 'blacklist', which is useful for studying human infectious diseases. OpenContami offers a comprehensive overview of exogenous species in NGS datasets; as such, it will increase our understanding of the impact of microbial contamination on biological and pathological traits.
OpenContami is freely available at: https://openlooper.hgc.jp/opencontami/.
Supplementary data are available at Bioinformatics online.
在生物实验过程中，微生物会感染和污染真核细胞。由于微生物会影响宿主细胞的生物学特性，因此可能导致错误的结论，所以需要一个能够促进净化的计算平台。最近的研究表明，下一代测序（NGS）数据可用于鉴定外源性微生物物种的存在。此前，我们提出了一种改进 NGS 数据中微生物检测的算法。在此，我们开发了一个在线应用程序 OpenContami，通过交互式网络界面为研究人员提供了方便访问该算法的途径。我们通过整合一个包含大规模公共数据集的分析结果和用户上传数据的数据库来设计该应用程序。该数据库可作为评估用户数据的参考，并提供从阴性空白对照中检测到的属列表作为“黑名单”，这对于研究人类传染病非常有用。OpenContami 提供了 NGS 数据集中外源物种的全面概述；因此，它将增进我们对微生物污染对生物学和病理学特征的影响的理解。
OpenContami 可在以下网址免费获得：https://openlooper.hgc.jp/opencontami/。
补充数据可在 Bioinformatics 在线获得。
