Plot response data

Usage

plot_resp(
  df,
  region_boundary,
  group_boundary = NULL,
  assay_quantiles = c(Median = 0.5),
  summary_quantiles = c(`10th percentile` = 0.1)
)

Arguments

df: output from resp_quantiles.
region_boundary: "sf" data.frame mapping features to a "geometry" column. Used to color map regions.
group_boundary: "sf" data.frame containing a "geometry" column. Used to draw outlines around groups of regions.
assay_quantiles: named numeric vector of assay quantile labels.
summary_quantiles: named numeric vector of summary quantile labels.

Value

ggplot2 object.

Examples

# Use example boundary data from package
region_boundary <- geo_tox_data$boundaries$county
group_boundary <- geo_tox_data$boundaries$state
n <- nrow(region_boundary)

# Single assay quantile
df <- data.frame(id = region_boundary$FIPS,
                 metric = "GCA.Eff",
                 assay_quantile = 0.5,
                 value = runif(n)^3)
# Default plot
plot_resp(df, region_boundary)

# Add group boundary, a state border in this case
plot_resp(df, region_boundary, group_boundary)

# Change quantile label
plot_resp(df, region_boundary, group_boundary,
          assay_quantiles = c("Q50" = 0.5))


# Multiple assay quantiles
df <- data.frame(id = rep(region_boundary$FIPS, 2),
                 metric = "GCA.Eff",
                 assay_quantile = rep(c(0.25, 0.75), each = n),
                 value = c(runif(n)^3, runif(n)^3 + 0.15))
plot_resp(df, region_boundary, group_boundary,
          assay_quantiles = c("Q25" = 0.25, "Q75" = 0.75))


# Summary quantiles
df <- data.frame(id = rep(region_boundary$FIPS, 4),
                 assay_quantile = rep(rep(c(0.25, 0.75), each = n), 2),
                 summary_quantile = rep(c(0.05, 0.95), each = n * 2),
                 metric = "GCA.Eff",
                 value = c(runif(n)^3, runif(n)^3 + 0.15,
                           runif(n)^3 + 0.7, runif(n)^3 + 0.85))
plot_resp(df, region_boundary, group_boundary,
          assay_quantiles = c("A_Q25" = 0.25, "A_Q75" = 0.75),
          summary_quantiles = c("S_Q05" = 0.05, "S_Q95" = 0.95))