--- title: "GeoTox Introduction" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{GeoTox Introduction} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` This vignette covers basic use of package functions. Package data, `geo_tox_data`, is used throughout the examples and details on how it was created can be found in the "GeoTox Package Data" vignette. ```{r setup, message=FALSE} library(GeoTox) library(dplyr) n <- 250 # Sample size ``` > **NOTE:** The sample size here is the size of the simulated population in each region. This is different than the sample size in the "package_data" vignette, which is used to generate `C_ss` values for each chemical at specified age and weight combinations. ## Analysis of single assay Create GeoTox object, run simulations and computations ```{r} set.seed(2357) geoTox <- GeoTox() |> # Set region and group boundaries (for plotting) set_boundaries(region = geo_tox_data$boundaries$county, group = geo_tox_data$boundaries$state) |> # Simulate populations for each region simulate_population(age = split(geo_tox_data$age, ~FIPS), obesity = geo_tox_data$obesity, exposure = split(geo_tox_data$exposure, ~FIPS), simulated_css = geo_tox_data$simulated_css, n = n) |> # Estimated Hill parameters set_hill_params(geo_tox_data$dose_response |> filter(endp == "TOX21_H2AX_HTRF_CHO_Agonist_ratio") |> fit_hill(chem = "casn") |> filter(!tp.sd.imputed, !logAC50.sd.imputed)) |> # Calculate response calculate_response() |> # Perform sensitivity analysis sensitivity_analysis() geoTox ``` Plot outputs ```{r, fig.width = 7, fig.height = 3, fig.align = 'center'} plot(geoTox) plot(geoTox, type = "hill") plot(geoTox, type = "sensitivity") ``` ## Analysis of multiple assay Create GeoTox object, run simulations and computations ```{r} set.seed(2357) geoTox <- GeoTox() |> # Set region and group boundaries (for plotting) set_boundaries(region = geo_tox_data$boundaries$county, group = geo_tox_data$boundaries$state) |> # Simulate populations for each region simulate_population(age = split(geo_tox_data$age, ~FIPS), obesity = geo_tox_data$obesity, exposure = split(geo_tox_data$exposure, ~FIPS), simulated_css = geo_tox_data$simulated_css, n = n) |> # Estimated Hill parameters set_hill_params(geo_tox_data$dose_response |> fit_hill(assay = "endp", chem = "casn") |> filter(!tp.sd.imputed, !logAC50.sd.imputed)) |> # Calculate response calculate_response() |> # Perform sensitivity analysis sensitivity_analysis() geoTox ``` Plot outputs ```{r, fig.width = 7, fig.height = 3, fig.align = 'center'} plot(geoTox) plot(geoTox, assays = "TOX21_H2AX_HTRF_CHO_Agonist_ratio") plot(geoTox, type = "hill") plot(geoTox, type = "sensitivity") plot(geoTox, type = "sensitivity", assay = "TOX21_H2AX_HTRF_CHO_Agonist_ratio") ``` ## Exposure Map The exposure map is the same for both single and multiple assay analyses. The map shows the distribution of chemical exposure across regions for all chemicals, not just those used in a particular analysis. ```{r, fig.width = 7, fig.height = 3, fig.align = 'center'} plot(geoTox, type = "exposure", ncol = 5) ``` If other facet labels are present they can be specified using the `chem_label` argument. ```{r, fig.width = 7, fig.height = 3, fig.align = 'center'} plot(geoTox, type = "exposure", chem_label = "chnm", ncol = 5) ```