German Cancer Research Center (DKFZ), Div Signaling and Functional Genomics and University of Heidelberg, Faculty of Medicine Mannheim, Dept Cell and Molecular Biology, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany.
BMC Bioinformatics. 2010 Apr 12;11:185. doi: 10.1186/1471-2105-11-185.
The analysis of high-throughput screening data sets is an expanding field in bioinformatics. High-throughput screens by RNAi generate large primary data sets which need to be analyzed and annotated to identify relevant phenotypic hits. Large-scale RNAi screens are frequently used to identify novel factors that influence a broad range of cellular processes, including signaling pathway activity, cell proliferation, and host cell infection. Here, we present a web-based application utility for the end-to-end analysis of large cell-based screening experiments by cellHTS2.
The software guides the user through the configuration steps that are required for the analysis of single or multi-channel experiments. The web-application provides options for various standardization and normalization methods, annotation of data sets and a comprehensive HTML report of the screening data analysis, including a ranked hit list. Sessions can be saved and restored for later re-analysis. The web frontend for the cellHTS2 R/Bioconductor package interacts with it through an R-server implementation that enables highly parallel analysis of screening data sets. web cellHTS2 further provides a file import and configuration module for common file formats.
The implemented web-application facilitates the analysis of high-throughput data sets and provides a user-friendly interface. web cellHTS2 is accessible online at http://web-cellHTS2.dkfz.de. A standalone version as a virtual appliance and source code for platforms supporting Java 1.5.0 can be downloaded from the web cellHTS2 page. web cellHTS2 is freely distributed under GPL.
高通量筛选数据集的分析是生物信息学中一个不断发展的领域。通过 RNAi 进行的高通量筛选会产生大量的原始数据集，这些数据集需要进行分析和注释，以识别相关的表型命中。大规模的 RNAi 筛选经常用于识别影响广泛细胞过程的新因素，包括信号通路活性、细胞增殖和宿主细胞感染。在这里，我们展示了一个基于网络的应用程序，用于通过 cellHTS2 对大型基于细胞的筛选实验进行端到端分析。
该软件引导用户完成分析单通道或多通道实验所需的配置步骤。该网络应用程序提供了各种标准化和归一化方法的选项，数据集的注释以及筛选数据分析的综合 HTML 报告，包括排名命中列表。会话可以保存并恢复以供以后重新分析。用于 cellHTS2 R/Bioconductor 包的网络前端通过 R-server 实现与之交互，该实现允许对筛选数据集进行高度并行分析。web cellHTS2 还提供了一个用于常见文件格式的文件导入和配置模块。
实现的网络应用程序简化了高通量数据集的分析，并提供了用户友好的界面。web cellHTS2 可在线访问，网址为 http://web-cellHTS2.dkfz.de。作为虚拟设备的独立版本和支持 Java 1.5.0 的平台的源代码可以从 web cellHTS2 页面下载。web cellHTS2 是根据 GPL 免费分发的。
