Beyond IC50s: Towards Robust Statistical Methods for in vitro Association Studies
Author(s) -
Alison A. MotsingerReif
Publication year - 2014
Publication title -
journal of pharmacogenomics and pharmacoproteomics
Language(s) - English
Resource type - Journals
ISSN - 2153-0645
DOI - 10.4172/2153-0645.1000121
Subject(s) - association (psychology) , computer science , inflection point , computational biology , genetic association , statistics , data mining , econometrics , mathematics , biology , psychology , genetics , genotype , geometry , gene , single nucleotide polymorphism , psychotherapist
Cell line cytotoxicity assays have become increasingly popular approaches for genetic and genomic studies of differential cytotoxic response. There are an increasing number of success stories, but relatively little evaluation of the statistical approaches used in such studies. In the vast majority of these studies, concentration response is summarized using curve-fitting approaches, and then summary measure(s) are used as the phenotype in subsequent genetic association studies. The curve is usually summarized by a single parameter such as the curve’s inflection point (e.g. the EC/IC 50 ). Such modeling makes major assumptions and has statistical limitations that should be considered. In the current review, we discuss the limitations of the EC/IC 50 as a phenotype in association studies, and highlight some potential limitations with a simulation experiment. Finally, we discuss some alternative analysis approaches that have been shown to be more robust.
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