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Published in

Oxford University Press, Bioinformatics, 2021

DOI: 10.1093/bioinformatics/btab043

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Comparison Of Observation-Based And Model-Based Identification Of Alert Concentrations From Concentration-Expression Data

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Motivation An important goal of concentration–response studies in toxicology is to determine an ‘alert’ concentration where a critical level of the response variable is exceeded. In a classical observation-based approach, only measured concentrations are considered as potential alert concentrations. Alternatively, a parametric curve is fitted to the data that describes the relationship between concentration and response. For a prespecified effect level, both an absolute estimate of the alert concentration and an estimate of the lowest concentration where the effect level is exceeded significantly are of interest. Results In a simulation study for gene expression data, we compared the observation-based and the model-based approach for both absolute and significant exceedance of the prespecified effect level. Results show that, compared to the observation-based approach, the model-based approach overestimates the true alert concentration less often and more frequently leads to a valid estimate, especially for genes with large variance. Availability and implementation The code used for the simulation studies is available via the GitHub repository: https://github.com/FKappenberg/Paper-IdentificationAlertConcentrations. Supplementary information Supplementary data are available at Bioinformatics online.