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library(tidyverse)
library(ggpubr)
data_simon <- read_csv("../csv/simon_data_extra.csv", na = "NULL")
data_mike <- read_csv("../csv/mike_repeat_visit.csv", na = "NULL")
f <- function(x, height = 0.05) {
ans <- median(x)
data.frame(ymin = ans - height / 2, ymax = ans + height / 2, y = ans)
}
simon_year_class <- data_simon %>%
select(donor_id, year, outcome, hai_response) %>%
mutate(outcome = factor(outcome, levels = c(1, 0), labels = c("H", "L"))) %>%
mutate(year_flag = year) %>%
mutate(outcome_flag = outcome) %>%
group_by(year, outcome) %>%
summarise(
year_flag = year_flag,
outcome_flag = outcome_flag,
donor_id = donor_id,
response = hai_response
)
simon_year_class
xlabels <- simon_year_class %>%
group_map(
~ {
rep(paste(.$outcome_flag[1], "\nn=(", length(unique(.$donor_id)), ")"), nrow(.))
}
)
count_high_and_low <- data_simon %>%
group_by(outcome) %>%
summarise(
count = length(unique(donor_id))
)
simon_plt <- simon_year_class %>%
ungroup() %>%
mutate(label = unlist(xlabels)) %>%
ggplot(aes(label, log2(response))) +
geom_violin(aes(fill = outcome, color = outcome), alpha = 0.2, show.legend = F) +
geom_boxplot(width = 0.1, show.legend = F) +
stat_summary(
fun.data = f, geom = "crossbar",
colour = NA, fill = "black", width = 0.3, alpha = 1.0
) +
geom_point(aes(fill = outcome), color = "black", shape = 23, show.legend = F) +
facet_grid(cols = vars(year), scales = "free") +
theme_pubclean() +
labs(x = "", y = "Log2 HAI response difference", title = paste(
"Donor first visit data used in SIMON, total=(", length(unique(simon_year_class$donor_id)), ")",
", high=(", count_high_and_low[2,2], ")", ", low=(", count_high_and_low[1,2],")"
))
mike_repeat_visits <- data_mike %>%
mutate(year_flag = year) %>%
group_by(donor_id, outcome) %>%
summarise(
count = length(unique(year_flag)),
outcome = unique(outcome)
) %>%
arrange(donor_id) %>%
ungroup()
mike_repeat_visits
repeat_plt <- mike_repeat_visits %>%
transmute(
second = sum(count >= 1),
third = sum(count >= 2),
fourth = sum(count >= 3),
fifth = sum(count >= 5)
) %>%
pivot_longer(
names_to = "visit",
values_to = "count",
cols = everything()
) %>%
slice(1:4, ) %>%
ggplot(aes(factor(visit, levels=c("second", "third", "fourth", "fifth")), count, fill = visit)) +
geom_bar(stat="identity", show.legend=F) +
labs(x = "Repeat visit number", y = "Number of donors") +
theme_pubclean()
repeat_plt
mike_second_visit <- data_mike %>%
group_by(donor_id) %>%
filter(year == min(year))
mike_second_visit
mike_second_visit_year_class <- mike_second_visit %>%
select(donor_id, year, outcome, hai_response) %>%
mutate(outcome = factor(outcome, levels = c(1, 0), labels = c("H", "L"))) %>%
mutate(year_flag = year) %>%
mutate(outcome_flag = outcome) %>%
group_by(year, outcome) %>%
summarise(
year_flag = year_flag,
outcome_flag = outcome_flag,
donor_id = donor_id,
response = hai_response
)
xlabels_mike <- mike_second_visit_year_class %>%
group_map(
~ {
rep(paste(.$outcome_flag[1], "\nn=(", length(unique(.$donor_id)), ")"), nrow(.))
}
)
count_high_and_low_mike <- mike_second_visit %>%
group_by(outcome) %>%
summarise(
count = length(unique(donor_id))
)
f <- function(x, height = 0.02) {
ans <- median(x)
data.frame(ymin = ans - height / 2, ymax = ans + height / 2, y = ans)
}
mike_plt <- mike_second_visit_year_class %>%
ungroup() %>%
mutate(label = unlist(xlabels_mike)) %>%
ggplot(aes(label, log2(response))) +
geom_violin(aes(fill = outcome, color = outcome), alpha = 0.2, show.legend = F) +
geom_boxplot(width = 0.1, show.legend = F) +
stat_summary(
fun.data = f, geom = "crossbar",
colour = NA, fill = "black", width = 0.3, alpha = 1.0
) +
geom_point(aes(fill = outcome), color = "black", shape = 23, show.legend = F) +
facet_grid(cols = vars(year), scales = "free") +
theme_pubclean() +
labs(x = "", y = "Log2 HAI response difference", title = paste(
"Donor second visit data used in this work, total=(", length(unique(mike_second_visit_year_class$donor_id)), ")",
", high=(", count_high_and_low_mike[2,2], ")", ", low=(", count_high_and_low_mike[1,2],")"
))
mike_plt
bottom <- ggarrange(
repeat_plt,
mike_plt,
ncol=2,
widths=c(1,2),
labels=c("B", "C")
)
whole <- ggarrange(
simon_plt,
bottom,
nrow=2,
heights=c(1,1),
labels=c("A", "")
)
ggsave("../images/data_selection.png", whole, width = 2 * 15, height = 19, dpi=300, units = "cm")
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