Beyond IC50s: Towards Robust Statistical Methods for in vitro Association Studies

Copyright: © 2013 Beam A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Discussion Association mapping (with either DNA level variation or gene expression data) in pharmacogenomics has been impeded by the reliance on clinical trials for samples. Genetic studies nested within clinical trials face the limited ability to enroll enough human subjects, ethical constraints, and the presence of uncontrolled confounders all of which may limit the capability to identify loci involved in drug-response [1]. To address these limitations, in vitro association studies have been proposed as an alternative to human-based studies because they address many of these concerns for certain types of drugs [1,2]. Cell-based studies offer extremely larg