Comparison of observation-based and model-based identification of alert concentrations from concentration–expression data
| Autor: | Marianna Grinberg, Jan G. Hengstler, Franziska Kappenberg, Annette Kopp-Schneider, Jörg Rahnenführer, Xiaoqi Jiang |
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| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Supplementary data AcademicSubjects/SCI01060 Gene Expression Variance (accounting) 010501 environmental sciences Original Papers 01 natural sciences Biochemistry Computer Science Applications 010104 statistics & probability Computational Mathematics Variable (computer science) Identification (information) Critical level Computational Theory and Mathematics Expression data Statistics 0101 mathematics Molecular Biology 0105 earth and related environmental sciences Mathematics |
| Zdroj: | Bioinformatics Bioinformatics, 37(14):1990-1996 |
| ISSN: | 1460-2059 1367-4803 |
| DOI: | 10.1093/bioinformatics/btab043 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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