toxpiR Introduction


This document introduces ToxPi and describes how to use the toxpiR package to easily import, recombine, analyze, and visualize high dimensional data. The toxpiR package is an R implementation of ToxPi that offers new features over what was previously available for data handling, recombination, and customization; provides formally packaged, open-source code for ToxPi; extends the application domain by supporting rapid analysis of massive datasets; and bridges with the stand-alone, Graphical User Interface (GUI) Java application and ArcGIS Toolkit.

What is ToxPi?

Toxicological Priority Index (ToxPi) is a decision support tool that allows transparent integration and visualization of data across disparate information domains to aid in prioritization. ToxPi takes input data of disparate sources,from a biological assay or a computer predicted model,to genetic features or proteomic data, and combines all of these data types into one overall model. This model then calculates an overall score for each datapoint of interest. It does this by the user specifying one or more features to go into each “slice” of a unit circle, and the weights that these slices have. These slices can contain one or more features of any type in the same slice. The slice weights are user defined, and decided based on prior information that one may have about the analysis. When a slice has a higher weight, it takes up more room on the unit square. When a slice has a higher calculated score, it goes further out from the center of the circle. As shown below, a feature with a low score will have overall smaller slices than one with an overall higher score. This means that we can understand at a glance the top level differences between what we are interested in. The component slices also add up to the overall ToxPi score with the weights add importance to that specific slice. The metrics that make up each component slice are simulated in data in this case, but can be many different kinds of data that fits your own analysis. More information on the methodological details can be found at