In mikeod38/ProvidenciaChemo:

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(message = FALSE)
knitr::opts_chunk$set(warning = FALSE)
library(ProvidenciaChemo)
library(tidyverse)
theme_set(theme_classic())

print(getwd())
egl <- read_csv('../data/egg_laying.csv') %>%
  mutate(strain = fct_relevel(food, c("OP50", "JUb39")),
         food = fct_relevel(food, "OP50", "JUb39"),
                              animal = interaction(genotype, group, food, animal_num))

counts <- egl %>%
  group_by(genotype, food) %>%
  summarize(grand_total = sum(number))

egl_summary <- egl %>%
  group_by(genotype, food, stage) %>%
  summarize(total_eggs = sum(number)) %>%
  full_join(., counts) %>%
  mutate(prop_eggs = total_eggs / grand_total)

counts_by_animal <- egl %>%
  group_by(genotype, food, animal) %>%
  summarize(grand_total = sum(number))

egl_summary_by_animal <- egl %>%
  group_by(genotype, food, stage, animal, group) %>%
  summarize(total_eggs = sum(number)) %>%
  full_join(., counts_by_animal) %>%
  mutate(prop_eggs = total_eggs / grand_total) %>%
  mutate(
    egg_stage = case_when(
      stage == "1-2" ~ "1-2",
      TRUE ~ "4+"
    ),
    groupID = interaction(genotype, food)
  )

egl_summary_by_animal %>%
  filter(stage == "1-2") %>%
  lme4::glmer(data = ., 
              cbind(total_eggs, (grand_total - total_eggs)) ~ groupID + (1|animal), 
              family = binomial) %>%
  emmeans::emmeans(~groupID) %>% emmeans::contrast(method = "pairwise")

egl_summary_by_animal %>%
  lme4::glmer(data = ., 
              grand_total ~ groupID + (1|animal), 
              family = poisson) %>%
  emmeans::emmeans(~groupID) %>% emmeans::contrast(method = "pairwise")
# 
# p3 <- egl %>%
#   group_by(genotype, food, animal) %>%
#   summarize(n_eggs = sum(number)) %>%
#   ggplot(aes(x = food, y = n_eggs)) +
#   ggbeeswarm::geom_quasirandom(aes(colour = interaction(food, genotype)), width = 0.2) +
#   stat_summary(aes(group = interaction(food, genotype)), geom = "errorbar", fun.data = "mean_se", width = 0.1) +
#   stat_summary(aes(group = interaction(food, genotype)), 
#                geom = "crossbar", 
#                fun.ymin = "mean", 
#                fun.ymax = "mean", 
#                fun.y = "mean",
#                width = 0.2) +
#   scale_color_plot(palette = "2-each", 
#                   drop = TRUE) +
#   facet_grid(.~genotype, scales = "free_x") +
#   guides(color = FALSE)

p4 <- egl_summary_by_animal %>%
  filter(egg_stage == "4+") %>%
  ggplot(aes(x = groupID, y = prop_eggs)) +
  geom_boxplot(aes(fill = groupID), outlier.shape = NA, alpha = 0.5) +
  ggbeeswarm::geom_quasirandom(width = 0.2, aes(colour = groupID)) +
  scale_fill_manual(values = c("#827E7E", "#B8B1B1", "#484CC7", "#2F8A34")) +
  scale_colour_manual(values = c("#827E7E", "#B8B1B1", "#484CC7", "#2F8A34")) +
labs(x = "condition", y = "proportion of eggs over 4-cell stage in utero")+
  scale_size_continuous(limits = c(5,25)) +
  theme(axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        panel.spacing = unit(2, "lines")) +
  add.n(groupID)


library(patchwork)
p4

mikeod38/ProvidenciaChemo documentation built on April 6, 2020, 11:57 p.m.