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Copy path27-02-2027_cass_BHRC_PrevByAge.R
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27-02-2027_cass_BHRC_PrevByAge.R
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pacman::p_load(
glue, dplyr, ggplot2, remotes,
envalysis, extrafont, glue, ggthemr,
tidyr
)
#font_import()
loadfonts()
# check system
if (Sys.info()["sysname"] == "Linux") {
Path <- "/media/santorolab/C207-3566"
font <- "Ubuntu Condensed"
} else {
Path <- "D:"
font <- "Arial Narrow"
}
# Data for models ajustment and plot
pheno <-
readRDS(glue("{Path}/objects_R/cass_BHRC_Mod_All_Phenotypes_26-02-2024.RDS"))$dcanyhk
ages <-
readRDS(glue("{Path}/objects_R/cass_BHRC_Age_Imputed_26-02-2024.RDS")) %>%
rename(age_W0 = W0, age_W1 = W1, age_W2 = W2)
prs <-
data.table::fread(glue("{Path}/PRS_database/Final_Scores_PRSCS/PRSCS_ADHD_Score.profile")) %>%
select(IID, PRSCS_zscore) %>%
rename(prs = PRSCS_zscore)
state <- readRDS(glue("{Path}/objects_R/cass_BHRC_STATE.RDS"))
sex <- readRDS(glue("{Path}/objects_R/cass_BHRC_sex.RDS"))
pc <- readRDS(glue("{Path}/objects_R/cass_BHRC_PC20.RDS"))
# Model ajustment
var_for_ajustment <- plyr::join_all(
list(prs, sex, state, pc),
by = "IID",
type = "inner"
)
new_values <- glm(prs ~ sex:PC20, data = var_for_ajustment)
new_prs <- data.frame(
IID = var_for_ajustment$IID,
prs = new_values$residuals
)
data_adhd <-
plyr::join_all(list(new_prs, pheno, ages), type = "inner", by = "IID")
# Prevalence calculation (10 and 5) and separate groups by age in W0
data_adhd$ADHD_Quintile <- ntile(data_adhd$prs, 5)
data_adhd <- select(data_adhd, -IID, -prs)
# Age
for_p0 <- table(round(data_adhd$age_W0), data_adhd$W0)
pW0 <-
as.data.frame(cbind(rownames(for_p0), for_p0)) %>%
rename(Age = V1, Control0 = 2, Case0 = 3) %>%
mutate(
across(Control0:Case0, as.numeric),
p0 = Case0 / (Case0 + Control0),
Age = as.numeric(Age)) %>%
select(-Control0, -Case0)
p0_data <- c(
mean = mean(pW0$p0), sd = sd(pW0$p0),
se = sd(pW0$p0)/sqrt(length(pW0)),
lower = t.test(pW0)$conf.int[1],
upper = t.test(pW0)$conf.int[2])
for_p1 <- table(round(data_adhd$age_W1), data_adhd$W1)
pW1 <-
as.data.frame(cbind(rownames(for_p1), for_p1)) %>%
rename(Age = V1, Control1 = 2, Case1 = 3) %>%
mutate(
across(Control1:Case1, as.numeric),
p1 = Case1 / (Case1 + Control1),
Age = as.numeric(Age)) %>%
select(-Control1, -Case1)
p1_data <- c(
mean = mean(pW1$p1), sd = sd(pW1$p1),
se = sd(pW1$p1)/sqrt(length(pW1)),
lower = t.test(pW1)$conf.int[1],
upper = t.test(pW1)$conf.int[2])
for_p2 <- table(round(data_adhd$age_W2), data_adhd$W2)
pW2 <-
as.data.frame(cbind(rownames(for_p2), for_p2)) %>%
rename(Age = V1, Control2 = 2, Case2 = 3) %>%
mutate(
across(Control2:Case2, as.numeric),
p2 = Case2 / (Case2 + Control2),
Age = as.numeric(Age)) %>%
select(-Control2, -Case2)
p2_data <- c(
mean = mean(pW2$p2), sd = sd(pW2$p2),
se = sd(pW2$p2)/sqrt(length(pW2)),
lower = t.test(pW2)$conf.int[1],
upper = t.test(pW2)$conf.int[2])
ggthemr("fresh")
# O problema de sobreposição de idades entre as waves AINDA
# é um troço que tá me fodendo e eu não sei como ajeitar
# Fazer um gráfico pra cada wave por idade
# outro exemplo: http://www.sthda.com/english/wiki/wiki.php?id_contents=7924
w0 <- ggplot(pW0, aes(x = Age, y = p0 * 100)) +
stat_smooth(
method = "lm",
formula = y ~ x,
geom = "smooth",
se = FALSE,
color = "#ff0000ef",
linetype = "dashed",
linewidth = 0.5) +
geom_point(size = 10, color = "#65ADC2") +
geom_line(linewidth = 3, color = "#65ADC2", alpha = 0.7) +
geom_errorbar(
aes(x = Age,
ymin = (p0 * 100) - p0_data[4],
ymax = (p0 * 100) + p0_data[5]),
position = position_dodge(0.05),
width = 0.3, linewidth = 1.5,
alpha = 0.6, color = "#65ADC2") +
scale_x_continuous(n.breaks = 9) +
scale_y_continuous(n.breaks = 10, limits = c(-5, 34)) +
theme_publish() +
labs(
title = "BHRC ADHD data prevalence by year in each wave",
subtitle = "W0",
y = "Prevalence %") +
theme(
text = element_text(family = font),
plot.background = element_rect(fill = "#ffffff"),
axis.title.y = element_blank(),
axis.text = element_text(face = "bold", size = 20),
legend.text = element_text(face = "italic", size = 20),
axis.title.x = element_blank(),
plot.subtitle = element_text(face = "bold", size = 25),
plot.title = element_text(face = "bold", size = 30))
w1 <- ggplot(pW1, aes(x = Age, y = p1 * 100)) +
stat_smooth(
method = "lm",
formula = y ~ x,
geom = "smooth",
se = FALSE,
color = "#ff0000ef",
linetype = "dashed",
linewidth = 0.5) +
geom_point(size = 10, color = "#233B43") +
geom_line(linewidth = 3, color = "#233B43", alpha = 0.7) +
geom_errorbar(
aes(x = Age,
ymin = (p1 * 100) - p1_data[4],
ymax = (p1 * 100) + p1_data[5]),
position = position_dodge(0.05),
width = 0.3, linewidth = 1.5,
alpha = 0.6, color = "#233B43") +
scale_x_continuous(n.breaks = 10) +
scale_y_continuous(n.breaks = 10, limits = c(-5, 34)) +
theme_publish() +
labs(subtitle = "W1", y = "Prevalence %") +
theme(
text = element_text(family = font),
plot.background = element_rect(fill = "#ffffff"),
axis.title.y = element_text(face = "bold", size = 25),
axis.title.x = element_blank(),
axis.text = element_text(face = "bold", size = 20),
legend.text = element_text(face = "italic", size = 20),
plot.subtitle = element_text(face = "bold", size = 25))
w2 <- ggplot(pW2, aes(x = Age, y = p2 * 100)) +
stat_smooth(
method = "lm",
formula = y ~ x,
geom = "smooth",
se = FALSE,
color = "#ff0000ef",
linetype = "dashed",
linewidth = 0.5) +
geom_point(size = 10, color = "#E84646") +
geom_line(linewidth = 3, color = "#E84646", alpha = 0.7) +
geom_errorbar(
aes(x = Age,
ymin = (p2 * 100) - p2_data[4],
ymax = (p2 * 100) + p2_data[5]),
position = position_dodge(0.05),
width = 0.3, linewidth = 1.5,
alpha = 0.5, color = "#E84646") +
scale_x_continuous(n.breaks = 11) +
scale_y_continuous(n.breaks = 10, limits = c(-5, 34)) +
theme_publish() +
labs(
subtitle = "W2",
x = "Age(yr)",
caption = "27-02-2024_cass_BHRC_PrevByAge.R") +
theme(
text = element_text(family = font),
plot.background = element_rect(fill = "#ffffff"),
axis.title = element_text(face = "bold", size = 20),
axis.text = element_text(face = "bold", size = 20),
axis.title.y = element_blank(),
legend.title = element_blank(),
plot.caption = element_text(size = 20),
plot.subtitle = element_text(face = "bold", size = 25))
final <- w0 / w1 / w2
final
library(patchwork)
colors <- c("#65ADC2", "#233B43", "#E84646")