RT Journal Article SR Electronic T1 PharmacoDB: an integrative database for mining in vitro drug screening studies JF bioRxiv FD Cold Spring Harbor Laboratory SP 195149 DO 10.1101/195149 A1 Smirnov, Petr A1 Kofia, Victor A1 Maru, Alexander A1 Freeman, Mark A1 Ho, Chantal A1 El-Hachem, Nehme A1 Adam, George-Alexandru A1 Ba-alawi, Wail A1 Safikhani, Zhaleh A1 Haibe-Kains, Benjamin YR 2017 UL http://biorxiv.org/content/early/2017/09/27/195149.abstract AB Recent pharmacogenomic studies profiled large panels of cancer cell lines against hundreds of approved drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbation, correlate these measures to genomic features, and thereby develop novel predictors of drug response. However, leveraging this valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale drug screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated pharmacogenomic datasets that are otherwise disparate and difficult to integrate.Key pointsCuration of cell line and drug identifiers in the largest pharmacogenomic studies published to dateUniform processing of drug sensitivity data to reduce heterogeneity across studiesMultiple drug response summary metrics enabling visual comparison and integrative analysis