PT - JOURNAL ARTICLE AU - Alina Malyutina AU - Jing Tang AU - Alberto Pessia TI - drda: An R package for dose-response data analysis AID - 10.1101/2021.06.07.447323 DP - 2021 Jan 01 TA - bioRxiv PG - 2021.06.07.447323 4099 - http://biorxiv.org/content/early/2021/06/07/2021.06.07.447323.short 4100 - http://biorxiv.org/content/early/2021/06/07/2021.06.07.447323.full AB - Analysis of dose-response data is an important step in many scientific disciplines, including but not limited to pharmacology, toxicology, and epidemiology. The R package drda is designed to facilitate the analysis of dose-response data by implementing efficient and accurate functions with a familiar interface. With drda, it is possible to fit models by the method of least squares, perform goodness of fit tests, and conduct model selection. Compared to other similar packages, drda provides, in general, more accurate estimates in the least-squares sense. This result is achieved by a smart choice of the starting point in the optimization algorithm and by implementing the Newton method with a trust region with analytical gradients and Hessian matrices. In this article, drda is presented through the description of its methodological components and examples of its user-friendly functions. Performance is finally evaluated using a real, large-scale drug sensitivity screening dataset.Competing Interest StatementThe authors have declared no competing interest.