Ling Alexander L, Zhang Weijie, Lee Adam, Xia Yunong, Su Mei-Chi, Gruener Robert F, Jena Sampreeti, Huang Yingbo, Pareek Siddhika, Shan Yuting, Stephanie Huang R
Harvey Cushing Neuro-oncology Laboratories, Department of Neurosurgery, Hale Building for Transformative Medicine, 4th and 8th floor, Brigham and Women's Hospital; 60 Fenwood Road, Boston, MA 02116.
Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN 55455, USA.
J Cancer Sci Clin Ther. 2023;7(4):249-252. doi: 10.26502/jcsct.5079217. Epub 2023 Dec 8.
High-throughput drug screens are a powerful tool for cancer drug development. However, the results of such screens are often made available only as raw data, which is intractable for researchers without informatics skills, or as highly processed summary statistics, which can lack essential information for translating screening results into clinically meaningful discoveries. To improve the usability of these datasets, we developed Simplicity, a robust and user-friendly web interface for visualizing, exploring, and summarizing raw and processed data from high- throughput drug screens. Importantly, Simplicity allows for easy recalculation of summary statistics at user-defined drug concentrations. This allows Simplicity's outputs to be used with methods that rely on statistics being calculated at clinically relevant doses. Simplicity can be freely accessed at https://oncotherapyinformatics.org/simplicity/.
高通量药物筛选是癌症药物开发的有力工具。然而，此类筛选的结果通常仅以原始数据的形式提供，这对于没有信息学技能的研究人员来说难以处理，或者以经过高度处理的汇总统计数据的形式提供，而这些汇总统计数据可能缺乏将筛选结果转化为具有临床意义的发现所需的关键信息。为了提高这些数据集的可用性，我们开发了Simplicity，这是一个强大且用户友好的网络界面，用于可视化、探索和汇总来自高通量药物筛选的原始数据和处理后的数据。重要的是，Simplicity允许在用户定义的药物浓度下轻松重新计算汇总统计数据。这使得Simplicity的输出结果能够与依赖于在临床相关剂量下计算统计数据的方法一起使用。可通过https://oncotherapyinformatics.org/simplicity/免费访问Simplicity。
