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.