In SilentSpringInstitute/RStateCancerProfiles: Download data from the U.S. State Cancer Profiles database

knitr::opts_chunk$set(echo = TRUE)

Mapping cancer incidence by county

library(RStateCancerProfiles)
library(tidyverse)
library(ggmap)
library(maps)

incidence <- cancer_statistics(statistic = "incidence")

incidence <- incidence %>%
  mutate(quantile = ntile(incidence_rate, 5))

fips <- county.fips %>%
  mutate(polyname = as.character(polyname))


incidence_with_geo <- map_data("county") %>%

  # Combine the region and subregion into one column so that we
  # can join with the county FIPS codes
  mutate(polyname = paste(region, subregion, sep=",")) %>%

  inner_join(fips, by = "polyname") %>%

  # Join in the incidence data, matching by FIPS
  inner_join(incidence, by="fips")

ggplot(incidence_with_geo, aes(x = long, y = lat, group = group)) +
  geom_polygon(aes(fill = as.factor(quantile))) +
  scale_fill_manual(values = c("#2C7BB6", "#ABD9E9", "#FFFFBF", "#FDAE61", "#D7191C")) +
  coord_map(projection = "albers", lat0 = 29.5, lat1 = 45.5) +
  theme_nothing()

Small multiples: county incidence maps for different cancer types

cancers <- c(
  "bladder",
  "brain & ONS",
  "breast (female)",
  "breast (female in situ)",
  "cervix",
  "colon & rectum",
  "esophagus",
  "kidney & renal pelvis",
  "leukemia",
  "liver & bile duct",
  "lung & bronchus",
  "non-hodgkin lymphoma",
  "melanoma of the skin",
  "oral cavity & pharynx",
  "ovary",
  "pancreas",
  "prostate",
  "stomach",
  "thyroid",
  "uterus"
)

incidence_list <- purrr::map(cancers, function(x) cancer_statistics(statistic = "incidence", cancer = x))

incidence <- incidence_list %>%
  bind_rows %>%
  group_by(cancer) %>%
  mutate(quantile = ntile(incidence_rate, 5)) %>%
  ungroup()

incidence_with_geo <- map_data("county") %>%
  mutate(polyname = paste(region, subregion, sep=",")) %>%
  inner_join(fips, by = "polyname") %>%
  inner_join(incidence, by="fips")


ggplot(incidence_with_geo, aes(x = long, y = lat, group = group)) +
  # County polygons
  geom_polygon(aes(fill = as.factor(quantile))) +

  # Set color scheme for the counties
  scale_fill_manual(values = c("#2C7BB6", "#ABD9E9", "#FFFFBF", "#FDAE61", "#D7191C")) +

  # Use a better map projection
  coord_map(projection = "albers", lat0 = 29.5, lat1 = 45.5) +

  # Create separate maps for different cancer types
  facet_wrap(~cancer, ncol = 5) +

  # Remove most chart elements, expect for titles for the
  # cancer types
  theme(legend.position = "none",
        line = element_blank(),
        rect = element_blank(),
        axis.text = element_blank(),
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        strip.text = element_text(size = 10))

SilentSpringInstitute/RStateCancerProfiles documentation built on May 9, 2019, 1:30 p.m.