ToxicR: A computational platform in R for computational toxicology and dose–response analyses
The need to analyze the complex relationships observed in high-throughput toxicogenomic and other omic platforms has resulted in an explosion of methodological advances in computational toxicology. However, advancements in the literature often outpace the development of software that researchers can implement in their pipelines, and existing software is frequently based on pre-specified workflows built from well-vetted assumptions that may not be optimal for novel research questions. Accordingly, there is a need for a stable platform and open-source codebase attached to a programming language that allows users to program new algorithms. In cooperation with the National Toxicology Program (NTP) and US Environmental Protection Agency (EPA), the National Institute of Environmental Health Sciences Biostatistics and Computational Biology Branch developed, an open-source R programming package to fill this gap ToxicR. The ToxicR platform implements many of the standard analyses in use by the NTP and EPA, including dose-response analyses for continuous and dichotomous data that employ Bayesian, maximum likelihood, and model averaging methods, as well as many standard tests the NTP uses in rodent toxicology and carcinogenicity studies such as the poly-K and Jonckheere trend tests. ToxicR is built on the same codebase as the current versions of the EPA's Benchmark Dose software and the NTP's BMDEExpress software, but because it directly accesses the software, the modeling platform has increased flexibility. To demonstrate ToxicR, we developed a custom workflow to illustrate its capabilities to analyze toxicogenomic data. The unique features of ToxicR will allow additional modules to be added by researchers in other fields, increasing its functionality in the future.