The hits_by_groupings_DT (DT option) and
hits_by_groupings (data frame option) functions create tables
with one row per category("Biological", "Chemical", or "Chemical Class").
The columns indicate the "Biological" groupings. The values in the table
signify how many sites have samples with EARs that exceeded the hit_threshold
for that particular "Biological"/category combination. If the user chooses
"Biological" as the category, it is a simple 2-column table of "Biological"
groupings and number of sites (nSites).
Usage
hits_by_groupings_DT(
chemical_summary,
category = "Biological",
mean_logic = FALSE,
sum_logic = TRUE,
hit_threshold = 0.1
)
hits_by_groupings(
chemical_summary,
category,
mean_logic = FALSE,
sum_logic = TRUE,
hit_threshold = 0.1
)Arguments
- chemical_summary
Data frame from
get_chemical_summary.- category
Character. Either "Biological", "Chemical Class", or "Chemical".
- mean_logic
Logical.
TRUEdisplays the mean sample from each site,FALSEdisplays the maximum sample from each site.- sum_logic
Logical.
TRUEsums the EARs in a specified grouping,FALSEdoes not.FALSEmay be better for traditional benchmarks as opposed to ToxCast benchmarks.- hit_threshold
Numeric threshold defining a "hit".
Details
The tables result in slightly different results for a single site, displaying the number of samples with hits rather than the number of sites.
Examples
# This is the example workflow:
path_to_tox <- system.file("extdata", package = "toxEval")
file_name <- "OWC_data_fromSup.xlsx"
full_path <- file.path(path_to_tox, file_name)
tox_list <- create_toxEval(full_path)
ACC <- get_ACC(tox_list$chem_info$CAS)
ACC <- remove_flags(ACC)
cleaned_ep <- clean_endPoint_info(end_point_info)
filtered_ep <- filter_groups(cleaned_ep)
chemical_summary <- get_chemical_summary(tox_list, ACC, filtered_ep)
site_df <- hits_by_groupings(chemical_summary, category = "Biological")
hits_by_groupings_DT(chemical_summary, category = "Biological")
hits_by_groupings_DT(chemical_summary, category = "Chemical Class")
hits_by_groupings_DT(chemical_summary, category = "Chemical")
