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Beyond IC(50)s: Towards Robust Statistical Methods for in vitro Association Studies

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 o...

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Detalles Bibliográficos
Autores principales: Beam, Andrew, Motsinger-Reif, Alison
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4125024/
https://www.ncbi.nlm.nih.gov/pubmed/25110614
http://dx.doi.org/10.4172/2153-0645.1000121
Descripción
Sumario: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.