Jackson Donald, Lenard Michael, Zelensky Alexander, Shaikh Mohammad, Scharpf James V, Shaginaw Richard, Nawade Mahesh, Agler Michele, Cloutier Normand J, Fennell Myles, Guo Qi, Wardwell-Swanson Judith, Zhao Dandan, Zhu Yingjie, Miller Christopher, Gill James
Applied Genomics Group, Applied Biotechnology Department, Bristol-Myers Squibb Research and Development, Princeton, NJ, USA.
J Biomol Screen. 2010 Aug;15(7):882-91. doi: 10.1177/1087057110374233. Epub 2010 Jul 16.
The effective analysis and interpretation of high-content screening (HCS) data requires joining results to information on experimental treatments and controls, normalizing data, and selecting hits or fitting concentration-response curves. HCS data have unique requirements that are not supported by traditional high-throughput screening databases, including the ability to designate separate positive and negative controls for different measurements in multiplexed assays; the ability to capture information on the cell lines, fluorescent reagents, and treatments in each assay; the ability to store and use individual-cell and image data; and the ability to support HCS readers and software from multiple vendors along with third-party image analysis tools. To address these requirements, the authors developed an enterprise system for the storage and processing of HCS images and results. This system, HCS Road, supports target identification, lead discovery, lead evaluation, and lead profiling activities. A dedicated client supports experimental design, data review, and core analyses and displays images together with results for assay development, hit assessment, and troubleshooting. Data can be exported to third-party applications for further analysis and exploration. HCS Road provides a single source for high-content results across the organization, regardless of the group or instrument that produced them.
对高内涵筛选（HCS）数据进行有效的分析和解读，需要将结果与实验处理及对照信息相结合、对数据进行归一化处理，以及选择命中结果或拟合浓度-响应曲线。HCS数据有一些传统高通量筛选数据库所不支持的独特要求，包括能够在多重分析中为不同测量指定单独的阳性和阴性对照；能够在每次分析中获取有关细胞系、荧光试剂和处理的信息；能够存储和使用单细胞及图像数据；以及能够支持来自多个供应商的HCS读数仪和软件以及第三方图像分析工具。为满足这些要求，作者开发了一个用于存储和处理HCS图像及结果的企业系统。这个名为HCS Road的系统支持靶点识别、先导物发现、先导物评估和先导物剖析活动。一个专用客户端支持实验设计、数据审查和核心分析，并将图像与用于分析方法开发、命中结果评估和故障排除的结果一起显示。数据可以导出到第三方应用程序进行进一步分析和探索。HCS Road为整个组织的高内涵结果提供了一个单一来源，无论这些结果是由哪个团队或仪器产生的。
