CurveCurator: A recalibrated F-statistic to assess, classify, and explore significance of dose-response curves

Abstract

AbstractDose-response curves are key metrics in pharmacology and biology to assess phenotypic or molecular actions of bioactive compounds in a quantitative fashion. Yet, it is often unclear whether or not a response significantly differs from a curve without regulation, particularly in high-throughput applications or unstable assays. Treating potency and effect size estimates from random and true curves with the same level of confidence can lead to incorrect hypotheses and issues in training machine learning models. Here, we present CurveCurator, an open-source software and interactive dashboard that provides reliable dose-response characteristics by computing p-values and false discovery rates based on a recalibrated F-statistic and a novel thresholding procedure. Application of CurveCurator to large-scale data sets demonstrates its scalable utility across several application areas.