plot_tox_heatmap {toxEval}

Plot EAR heat maps

Description

The plot_tox_heatmap function creates a heat (tile) map with sites on the x-axis, a specified grouping on the y-axis (defined by the category argument), and color shading defining the mean or maximum EAR. See "Summarizing the data" in the Introduction vignette: vignette("Introduction", package = "toxEval") for a description on how the EAR values are computed, aggregated, and summarized. The y-axis grouping can be "Biological", "Chemical Class", or "Chemical". When specifying the "Chemical" option, a secondary y-axis is automatically included to group chemicals into chemical class. The function computes default breaks for the color scale to match the spread of the data, but breaks can also be customized with the breaks argument. This is a function where it may be ideal to create a custom order to the sites (for example, west-to-east). See the above section "Custom configuration" vignette("Introduction", package = "toxEval") for instructions on how to convert the character vector sites to a factor with ordered levels.

Usage

plot_tox_heatmap(
  chemical_summary,
  chem_site,
  category = "Biological",
  breaks = c(1e-05, 1e-04, 0.001, 0.01, 0.1, 1, 10),
  manual_remove = NULL,
  mean_logic = FALSE,
  sum_logic = TRUE,
  plot_ND = TRUE,
  font_size = NA,
  title = NA,
  legend_lab = NA
)

Arguments

chemical_summary

Data frame from get_chemical_summary.

chem_site

Data frame with columns SiteID, site_grouping, and Short Name.

category

Either "Biological", "Chemical Class", or "Chemical".

breaks

Numerical vector to define data bins and legend breaks.

manual_remove

Vector of categories to remove.

mean_logic

Logical. TRUE displays the mean sample from each site, FALSE displays the maximum sample from each site.

sum_logic

Logical. TRUE sums the EARs in a specified grouping, FALSE does not. FALSE may be better for traditional benchmarks as opposed to ToxCast benchmarks.

plot_ND

Logical. Whether or not to plot "Biological" groupings, "Chemical Class" groupings, or "Chemical" that do not have any detections.

font_size

Numeric value to adjust the axis font size.

title

Character title for plot.

legend_lab

Character label for legend. Default is NA which produces an automatic label.

Details

If there are site/parameters (chemical/chemical class/biological grouping) combinations that don't have data, those areas are represented by an "X". If there are 0 values, they are considered "non-detects", and represented with a distinct color.

Examples

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)

# Order the site_groupings:
tox_list$chem_site$site_grouping <- factor(tox_list$chem_site$site_grouping,
  levels = c(
    "Lake Superior",
    "Lake Michigan",
    "Lake Huron",
    "Lake Erie",
    "Lake Ontario"
  )
)

# Order sites:
sitesOrdered <- c(
  "StLouis", "Nemadji", "WhiteWI", "Bad", "Montreal",
  "PresqueIsle", "Ontonagon", "Sturgeon", "Tahquamenon", "Burns",
  "IndianaHC", "StJoseph", "PawPaw", "Kalamazoo", "GrandMI",
  "Milwaukee", "Muskegon", "WhiteMI", "PereMarquette", "Manitowoc",
  "Manistee", "Fox", "Oconto", "Peshtigo", "Menominee",
  "Indian", "Cheboygan", "Ford", "Escanaba", "Manistique",
  "ThunderBay", "AuSable", "Rifle", "Saginaw", "BlackMI",
  "Clinton", "Rouge", "HuronMI", "Raisin", "Maumee",
  "Portage", "Sandusky", "HuronOH", "Vermilion", "BlackOH",
  "Rocky", "Cuyahoga", "GrandOH", "Cattaraugus", "Tonawanda",
  "Genesee", "Oswego", "BlackNY", "Oswegatchie", "Grass",
  "Raquette", "StRegis"
)

tox_list$chem_site$`Short Name` <- factor(tox_list$chem_site$`Short Name`,
  levels = sitesOrdered
)

plot_tox_heatmap(chemical_summary, 
                 tox_list$chem_site,
                 category = "Chemical Class")
              
plot_tox_heatmap(chemical_summary,
                 tox_list$chem_site,
                 category = "Chemical",
                 legend_lab = "EAR"
)

single_site <- dplyr::filter(chemical_summary, site == "USGS-04024000")

plot_tox_heatmap(
  chemical_summary = single_site,
  chem_site = dplyr::filter(tox_list$chem_site, 
                            SiteID == "USGS-04024000"),
  category = "Chemical Class"
)
plot_tox_heatmap(
  chemical_summary = single_site,
  chem_site = dplyr::filter(tox_list$chem_site, SiteID == "USGS-04024000"),
  category = "Chemical"
)