get_risk_values: Get risk metric results

In GeoTox: Spatiotemporal Mixture Risk Assessment

Get risk metric results

Description

Several functions used to fetch risk metric results from risk tables in a GeoTox database. The outputs of these functions are useful for plotting or further analysis.

Usage

get_assay_table(GT)

get_risk_quantiles(
  GT,
  metric = c("GCA.Eff", "IA.Eff", "GCA.HQ.10", "IA.HQ.10"),
  quantiles = c(0.1, 0.25, 0.5, 0.75, 0.9),
  table_name = "risk"
)

get_risk_sensitivity(
  GT,
  metric = c("GCA.Eff", "IA.Eff", "GCA.HQ.10", "IA.HQ.10"),
  assay = NULL
)

get_risk_values(
  GT,
  metric = c("GCA.Eff", "IA.Eff", "GCA.HQ.10", "IA.HQ.10"),
  assay = NULL,
  table_name = "risk"
)

Arguments

GT	GeoTox object.
metric	Risk metric to retrieve. One of "GCA.Eff", "IA.Eff", "GCA.HQ.10", or "IA.HQ.10".
quantiles	Numeric vector of quantiles to calculate.
table_name	Name of the risk table to query (default "risk").
assay	Named vector specifying an assay filter (default NULL).

Details

Normally an 'assay' table is created when adding the Hill model concentration-response fit parameters with add_hill_params(). If no assay input is specified in fit_hill(), then an 'assay' table will not be created. For get_risk_values(), the assay parameter can be used to filter results based on assay details stored in the 'assay' table. This is useful when multiple assays are available in the database. The assay input should be a named vector specifying the column name and value to filter by, e.g. assay = c(endp = "mortality"). For get_risk_quantiles(), if there is no assay data in the GeoTox database, then the output "assay_id" column will be filled with NA values. If there is assay data, use get_assay_table() to retrieve assay information and link the "assay_id" to assay details.

Use the table_name parameter to specify which risk table to query. There can be several risk tables in a GeoTox database. The default table is named "risk" and is created by either calc_risk() or the wrapper function calc_response(). Sensitivity analysis results created by either calc_sensitivity() or the wrapper function sensitivity_analysis() are stored in other tables with names like "risk_sensitivity_age", etc. Refer to calc_sensitivity() to see which tables may be available.

get_risk_sensitivity() is a wrapper function for get_risk_values() around all risk tables created by the original risk computation and subsequent sensitivity analysis. The column names are "baseline" for the original risk table, while the other column names correspond to the parameter varied in the sensitivity analysis.

Value

A data frame or vector.

See Also

calc_risk(), calc_response(), calc_sensitivity(), sensitivity_analysis(), fit_hill(), add_hill_params()

Examples

# Example setup is shown below in \dontrun().
# Pre-generated results will be loaded instead to avoid long example runtime.

## Not run: 
# Setup required tables
sample_df <- tibble::tribble(
  ~FIPS, ~age, ~weight,
  10000, 25, "Normal",
  10000, 35,  "Obese",
  20000, 50, "Normal"
)
exposure_df <- tibble::tribble(
  ~FIPS, ~casn, ~route, ~mean, ~sd,
  10000, "00-00-1", "inhalation", 10, 1,
  10000, "00-00-2", "inhalation", 20, 1,
  20000, "00-00-1", "inhalation", 30, 1,
  20000, "00-00-2", "inhalation", 40, 1
)
css_df <- tibble::tribble(
  ~casn, ~age_lb, ~age_ub, ~weight, ~css,
  "00-00-1",  0, 49, "Normal", 21,
  "00-00-1", 50, 99, "Normal", 22,
  "00-00-1",  0, 49,  "Obese", 61,
  "00-00-1", 50, 99,  "Obese", 62,
  "00-00-2",  0, 49, "Normal", 11,
  "00-00-2", 50, 99, "Normal", 12,
  "00-00-2",  0, 49,  "Obese", 31,
  "00-00-2", 50, 99,  "Obese", 32
)
hill_df <- tibble::tribble(
  ~assay, ~model, ~casn, ~logc, ~resp,
  "a1", "human", "00-00-1",    0,  10,
  "a1", "human", "00-00-1",    1,  20,
  "a1", "human", "00-00-1",    2,  80,
  "a1", "human", "00-00-1",    3, 100,
  "a1", "human", "00-00-2", -0.5,   5,
  "a1", "human", "00-00-2",  0.5,  20,
  "a1", "human", "00-00-2",  1.5,  55,
  "a1", "human", "00-00-2",  2.5,  60,
  "a2",   "rat", "00-00-1",   -1,   0,
  "a2",   "rat", "00-00-1",    0,  10,
  "a2",   "rat", "00-00-1",    1,  30,
  "a2",   "rat", "00-00-1",    2,  40
)
set.seed(1234)
GT <- GeoTox() |>
  set_sample(sample_df) |>
  set_simulated_css(css_df) |>
  add_exposure_rate_params() |>
  add_hill_params(fit_hill(
    hill_df, assay = c(name = "assay", model = "model"), substance = "casn"
  )) |>
  simulate_population(exposure = exposure_df) |>
  calc_response() |>
  sensitivity_analysis()

## End(Not run)

# Load results from pre-generated database for this example
temp_dir <- tempdir()
zip::unzip(
  system.file("extdata", "sensitivity.duckdb.zip", package = "GeoTox"),
  junkpaths = TRUE,
  exdir = temp_dir
)
GT <- GeoTox(paste0(temp_dir, "/sensitivity.duckdb"))

# Look at 'assay' table contents
get_assay_table(GT)

# Get "GCA.HQ.10" values from 'risk' table for the "a1" assay
get_risk_values(GT, metric = "GCA.HQ.10", assay = c(name = "a1"))

# Get "IA.Eff" values from all risk tables for the "a2" assay
get_risk_sensitivity(GT, metric = "IA.Eff", assay = c(name = "a2"))

# Get "GCA.Eff" quantiles from 'risk' table
get_risk_quantiles(GT, metric = "GCA.Eff", quantiles = c(0.25, 0.5, 0.75))

# Open a connection to GeoTox database
con <- get_con(GT)

# Look at the 'risk' table contents
dplyr::tbl(con, "risk") |> dplyr::collect()

# Clean up example
DBI::dbDisconnect(con)
file.remove(GT$db_info$dbdir)

GeoTox documentation built on May 20, 2026, 1:07 a.m.