library(ggplot2)
library(dplyr)
dat1 <- read.csv("20240913Rintest_dul-iso.csv", sep = ',', header = TRUE)
# Figure1d
library(ggplot2)
library(dplyr)
dat1 <- read.csv("20240902Rintest_dul-iso.csv", sep = ',', header = TRUE)
dat1 %>%
ggplot(aes(x = compound, y = FC)) +
geom_boxplot(outlier.shape = NA, )+
stat_boxplot(geom = "errorbar", width = 0.1) +
geom_jitter()+
theme(text = element_text(size = 13), axis.text.x = element_text(angle = 45,hjust = 1),
panel.background = element_rect(fill='white'),
panel.grid.major = element_line(color = "black", linewidth = 4),  # Adjust gridline color and size
panel.grid.minor = element_blank(),  # Remove minor gridlines
panel.grid.major.x = element_line(color = "grey", linewidth = 0.2),  # Color for x-axis major gridlines
panel.grid.major.y = element_line(color = "grey", linewidth = 0.2),   # Color for y-axis major gridlines
axis.line.x = element_line(colour = 'black', linewidth = 0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', linewidth = 0.5, linetype='solid')
)
View(dat1)
box_stats <- dat1 %>%
group_by(compound) %>%
summarise(
Q1 = quantile(FC, 0.25),
median = quantile(FC, 0.50),
Q3 = quantile(FC, 0.75),
IQR = IQR(FC),
lower_whisker = max(min(FC), Q1 - 1.5 * IQR),
upper_whisker = min(max(FC), Q3 + 1.5 * IQR),
minimum = min(FC),
maximum = max(FC)
)
write.csv(box_stats, "box_stats_Fig1d.csv")
View(box_stats)
write.csv(box_stats, "box_stats_detail_Fig1d.csv")
box_stats2 <- dat1 %>%
summarise(
Q1 = quantile(FC, 0.25),
median = quantile(FC, 0.50),
Q3 = quantile(FC, 0.75),
IQR = IQR(FC),
lower_whisker = max(min(FC), Q1 - 1.5 * IQR),
upper_whisker = min(max(FC), Q3 + 1.5 * IQR),
minimum = min(FC),
maximum = max(FC)
)
View(box_stats2)
write.csv(box_stats2, "box_stats_Fig1d.csv")
