The toxEval R-package
includes a set of functions to analyze, visualize, and organize measured
concentration data as it relates to ToxCast
data (default) 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. Full
documentation of this R package including a tutorial with examples is
available here: https://doi-usgs.github.io/toxEval/index.html
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. Documentation for the app is provided here.
This vignette provides a general overview of the concepts within
toxEval, definitions of common terminology used throughout
the package, and links to information to help understand fundamentals of
the ToxCast database used within toxEval.
The U.S. EPA’s Toxicity Forecaster
ToxCast
includes a database of chemical-biological interactions that contains
information from hundreds of assays on thousands of chemicals, providing
a means to assess biological relevance to measured concentrations. The
toxEval package attempts to simplify the workflow for
exploring data as it relates to these assay endpoints (benchmark data).
The workflow uses ToxCast as a default for evaluation of
chemical:biological interactions, but the user may also define
alternative benchmarks for a custom or more traditional approach to
biological relevance evaluation. This is also a useful capability for
efficient comparison of ToxCast evaluation results with those from other
toxicity benchmark databases.
When using the ToxCast endPoints for analysis, it is important to have at least a minimal understanding of what ToxCast data is, and which ToxCast data is relevant to any given study. There are many useful resources here. There is also a tool called the Comptox Dashboard that has a wealth of information on ToxCast data.
So what are we doing with the user input data and ToxCast? First, we calculate an Exposure-Activity Ratio (EAR) for each measurement. Then we can explore the EARs based on a wide variety of groupings to view the data in many dimensions.
An Exposure-Activity Ratio (EAR) is defined as the ratio of a
measured concentration and a concentration that was determined to cause
some activity in a specified ToxCast assay (“endPoint” concentration).
An EAR > 1.0 would indicate that the measured concentration is
greater than the endpoint concentration. The ToxCast database (as
provided in the current version of toxEval) provides as
many as several hundred endPoints for more than 7000 chemicals. Each
endPoint is a single test that was done to detect some form of
biological activity.
In order to get appropriate EAR results, it is important to use the
correct units. The toxEval package assumes all measured
concentrations are reported in micrograms per liter (μg/L). ToxCast data is reported in
log(μM), so the
toxEval package automatically performs the unit
conversion.
A secondary option within toxEval is for the user to
provide a set of “benchmark concentrations” to define custom biological
responses to meet specific study objectives (e.g. water quality
criteria). In this case, EAR values are replaced with toxicity
quotients. Similar to EAR values, toxicity quotients are defined as the
ratio of a measured concentration to the benchmark concentration.
EAR is basically synonymous with bioanalytical equivalent concentrations (BEQ). EAR is a ratio, and BEQ is a measure of concentration, but both convey the same information.
ToxCast uses high-throughput assays to create concentration-response
curves for each of these chemical: endPoint combinations. An endPoint is
“associated with the perturbation of specific biological processes
identified for the confirmation or monitoring of predicted site-specific
hazards” Blackwell 2017. That means a specific biological action was
tested, and the concentration at which activity was observed was
determined. Of several endpoint values provided within the ToxCast
database, the activity concentration at cutoff (ACC) was chosen to
compute EAR values within the toxEval package, consistent
with the description in Blackwell, 2017. ACC values from the ToxCast
database are provided within the toxEval package.
Often, it is valuable to consider aggregations of single endPoints in
evaluation efforts. ToxCast has provided tables that group individual
endPoints into generalized categories for functional use. The grouping
summary table is included in toxEval and can be explored
via the end_point_info data:
See the help file ?end_point_info for specifics on how
the table was downloaded.
Throughout the toxEval analysis, there are graphing and
table functions that will summarize EARs based on either “Biological”
groupings (as defined by a group of endPoints) or “Chemical Class”
groupings (as defined by a group of chemicals).
The default grouping of ToxCast endPoints is
“intended_target_family”, but depending on the analysis, it may be more
appropriate to use other grouping categories. To change the default,
specify a grouping in the groupCol argument of the
filter_groups function. For example:
filtered_ep <- filter_groups(end_point_info,
groupCol = "intended_target_family",
assays = c("ATG","NVS", "OT", "TOX21",
"CEETOX", "APR", "CLD", "TANGUAY",
"NHEERL_PADILLA","NCCT_SIMMONS", "ACEA"),
remove_groups = c("Background Measurement",
"Undefined"))What is happening here is that the supplied data frame
end_point_info is filtered to just the
“intended_target_family” group. Additionally, the assay BioSeek is
removed (it is the only one not included in the possible list of
assays). Finally, of all the groups within intended_target_family, the
end points designated “Undefined” and “Background Measurement” are
removed.
The functions in toxEval summarize the data as
follows:
First, individual EAR values are calculated for each
chemical:endPoint combination. Then, the EAR values are summed together
by samples (a sample is defined as a unique site/date) based on the
grouping picked in the “category” argument. Categories include
“Biological”, “Chemical Class”, or “Chemical”. “Biological” refers to
the chosen ToxCast annotation as defined in the groupCol
argument of the filter_groups function. “Chemical Class”
refers to the groupings of chemicals as defined in the “Class” column of
the “Chemicals” sheet of the input file. “Chemical” refers to the
individual chemical as defined by a unique CAS value. Finally, the
maximum or mean EAR is calculated per site (based on the
mean_logic option). This ensures that each site is
represented equally regardless of how many samples are available per
site.
Some functions will also include a calculation for a “hit”. A threshold is defined by the user, and if the mean or maximum EAR (calculated as described above) is greater than the threshold, that is considered a “hit”.
If you discover an issue that you feel is a bug in the package or have a question on functionality, please consider reporting bugs and asking questions on the Issues page: https://github.com/DOI-USGS/toxEval/issues
## 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,
## <https://CRAN.R-project.org/package=toxEval>.
##
## 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},
## url = {https://CRAN.R-project.org/package=toxEval},
## }