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toxEval toxEval

CRAN version

The toxEval R-package includes a set of functions to analyze, visualize, and organize measured concentration data as it relates to https://www.epa.gov/comptox-tools/toxicity-forecasting-toxcast or other user-selected chemical-biological interaction benchmark data such as water quality criteria. The intent of these analyses is to develop a better understanding of the potential biological relevance of environmental chemistry data. Results can be used to prioritize which chemicals at which sites may be of greatest concern. These methods are meant to be used as a screening technique to predict potential for biological influence from chemicals that ultimately need to be validated with direct biological assays.

The functions within this package allow great flexibly for exploring the potential biological affects of measured chemicals. Also included in the package is a browser-based application made from the Shiny R-package (the app). The app is based on functions within the R-package and includes many convenient analyses and visualization options for users to choose. Use of the functions within the R-package allows for additional flexibility within the functions beyond what the app offers and provides options for the user to interact more directly with the data. The overview in this document focuses on the R-package.

Installation of toxEval

To install the toxEval package, you must be using R 3.0 or greater and run the following command:

install.packages("toxEval")

To get cutting-edge changes, install from GitHub using the remotes packages:

library(remotes)
install_gitlab("water/toxEval",
               host = "code.usgs.gov",
               build_vignettes = TRUE, 
               build_opts = c("--no-resave-data",
                              "--no-manual"),
               dependencies = TRUE)

Quickstart

Installation instructions are below. To quickly get going in toxEval, run:

library(toxEval)
#> For more information:
#> https://doi-usgs.github.io/toxEval/
#> ToxCast database: version 4.1
explore_endpoints()

app_demo

Then click on the “Load Example Data” in the upper right corner. This loads the example data that is found here:

file.path(system.file("extdata", package="toxEval"), "OWC_data_fromSup.xlsx")

Once the data is loaded in the app, sample R code is shown below each tab. This can be copied into the R console (once the app is stopped…) to use as a base for exploring the package directly in R.

Alternatively, an example workflow is shown here (also using example data provided in the package):

library(toxEval)
path_to_file <- file.path(system.file("extdata", package="toxEval"), "OWC_data_fromSup.xlsx")
tox_list <- create_toxEval(path_to_file)
ACClong <- get_ACC(tox_list$chem_info$CAS)
ACClong <- remove_flags(ACClong)

cleaned_ep <- clean_endPoint_info(end_point_info)
filtered_ep <- filter_groups(cleaned_ep, 
                  groupCol = 'intended_target_family',
                  remove_groups = c('Background Measurement','Undefined'))

chemicalSummary <- get_chemical_summary(tox_list, 
                                        ACClong, 
                                        filtered_ep)
######################################
chem_class_plot <- plot_tox_boxplots(chemicalSummary,
                                     category = 'Chemical Class')
chem_class_plot

######################################
plot_stacks <- plot_tox_stacks(chemicalSummary, 
                               tox_list$chem_site, 
                               category = "Chemical Class")
plot_stacks

######################################
plot_heat <- plot_tox_heatmap(chemicalSummary, 
                              tox_list$chem_site, 
                              category = "Chemical Class",
                              font_size = 7)
plot_heat

This code opens up the example file, loads it into a toxEval object, grabs the pertinent ToxCast information, and creates a “chemicalSummary” data frame that is used in many of the plot and table functions.

There are 4 vignettes to help introduce and navigate the toxEval package:

Name R command Description
Introduction vignette("Introduction", package="toxEval") Introduction to the toxEval
Basic Workflow vignette("basicWorkflow", package="toxEval") Quickstart guide to get overview of available functions
Prepare Data vignette("PrepareData", package="toxEval") Guide to preparing your data for toxEval analysis
Shiny App Guide vignette("shinyApp", package="toxEval") Guide to the toxEval shiny application

Reporting bugs

Please consider reporting bugs and asking questions on the Issues page: https://github.com/DOI-USGS/toxEval/issues

Code of Conduct

We want to encourage a warm, welcoming, and safe environment for contributing to this project. See the code of conduct for more information.

Package Support

The Water and Environmental Health Mission Areas of the USGS, as well as the Great Lakes Restoration Initiative (GLRI) has supported the development of the toxEval R-package. Further maintenance is expected to be stable through September 2025. Resources are available primarily for maintenance and responding to user questions. Priorities on the development of new features are determined by the toxEval development team.

Sunset date

Funding for toxEval is secured through summer 2025, after which bug fixes & new features will be minimal.

Run toxEval

To run the toxEval app:

  1. Open RStudio
  2. In the Console (lower-left window of RStudio) paste the following:
library(toxEval)
explore_endpoints()

Citing toxEval

citation(package = "toxEval")
#> To cite package 'toxEval' in publications use:
#> 
#>   DeCicco L, Corsi S, Villeneuve D, Blackwell B, Ankley G (2024).
#>   _toxEval: Exploring Biological Relevance of Environmental Chemistry
#>   Observations_. R package version 1.4.0.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {toxEval: Exploring Biological Relevance of Environmental Chemistry
#> Observations},
#>     author = {Laura DeCicco and Steven Corsi and Daniel Villeneuve and Brett Blackwell and Gerald Ankley},
#>     year = {2024},
#>     note = {R package version 1.4.0},
#>   }