GeoTox open-source R software package for characterizing the risk of
perturbing molecular targets involved in adverse human health outcomes
based on exposure to spatially-referenced stressor mixtures via the
GeoTox framework - otherwise known as source-to-outcome-continuum
modeling. The package, methods, and case-studies are described in
Messier, Reif, and Marvel, 2024,
medRxiv-Preprint.
The GeoTox framework was first described in Eccles et al. A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target. Sci Total Environ. 2023 Jan 10;855:158905.
The package will be on CRAN in the near future - please stay tuned.
The development version can be installed from GitHub with:
#install.packages("pak")
pak::pak("NIEHS/GeoTox")Figure 1 below shows the steps in the source-to-outcome-continuum or
GeoTox modelling framework that is capable in the GeoTox package.
blue text nodes represent an object
and green text, rounded nodes
represent a methodology or function required to go from one to the next.
The GeoTox package uses R S3 object-oriented programming to create the
GeoTox object. The GeoTox object is a list that contains all of
the information required to run the analysis including tracking
exposure, assays, dose-response, and geospatial referencing.
Figure 1: Overview of the steps in the GeoTox framework
Please refer to the introduction
vignette for
a detailed description of how to use GeoTox.
For citation information, please refer to our CITATION file.
To add or edit functionality, open a pull request into the main branch with a detailed description of the proposed changes. Pull requests must pass all status checks, and then will be approved or rejected by the GeoTox maintainers.
Utilize GitHub issues to notify the authors of bugs, questions, or recommendations. Identify each issue with the appropriate label to help ensure a timely response.