Assessing consistency across functional screening datasets in cancer cells

Many high-throughput screening studies have been carried out in cancer cell lines to identify therapeutic agents and targets. Existing consistency assessment studies only examined two datasets at a time, with conclusions based on a subset of carefully selected features rather than considering global consistency of all the data. In this study we assembled nine compound screening datasets and three functional genomics datasets, and derived direct measures of consistency as well as indirect measures of consistency based on association between functional data and copy number-adjusted gene expression data. These results have been integrated into a web application – the Functional Data Consistency Explorer (FDCE), to allow users to make queries and generate interactive visualizations so that functional data consistency can be assessed for individual features of interest.既往已有多项针对癌细胞系的高通量筛选（high-throughput screening）研究，旨在鉴定治疗性药物与靶点。现有一致性评估研究仅单次针对两个数据集开展，其结论仅基于精心筛选的特征子集，未考量全数据的全局一致性。本研究整合了9个化合物筛选数据集与3个功能基因组学（functional genomics）数据集，并基于功能数据与拷贝数校正的基因表达数据间的关联，推导得到一致性的直接测度与间接测度。本研究结果已整合至一款名为功能数据一致性探索器（Functional Data Consistency Explorer, FDCE）的Web应用中，该工具支持用户发起查询并生成交互式可视化图表，以便针对目标个体特征开展功能数据一致性评估。