Kappenberg F, Grinberg M, Jiang X, Kopp-Schneider A, Hengstler JG, Rahnenführer J. Comparison Of Observation-Based And Model-Based Identification Of Alert Concentrations From Concentration-Expression Data.
Bioinformatics 2021;
37:1990–1996. [PMID:
33515236 PMCID:
PMC8337003 DOI:
10.1093/bioinformatics/btab043]
[Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 01/15/2021] [Accepted: 01/18/2021] [Indexed: 11/23/2022] Open
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.
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