Loop violin plots of controls with clinical case data points overlaid (ggplot) - r

Question

New to posting on here. Apologies if I miss including something needed to solve my situation.
I have a matched case-control design where three 'younger' clinical cases have been age-matched to a 'younger' control group, and three 'older' cases have been matched to an 'older' control group. I am plotting the control group distribution in a violin plot and overlaying the corresponding matched cases as data points.
I have a lot of variables and I would like to loop through them to minimise error and increase efficiency. I have had a go at writing the code for the loop but I am not sure what to do with the fact that I have two types of plots (violin and point) and two data frames (controls and cases) involved.
Here is the code I have for the plots:
#fake data
cases <- data.frame(
id = factor(1:6),
strange_stories_ToM_mean = sample(6:8, 6, replace = TRUE),
age = factor(c(rep("young", 3), rep("old", 3)))
)
controls <- data.frame(
id = 7:23,
strange_stories_ToM_mean = sample(c(6,6,7,7,7,7,7,7,7,8,8,8,9,9,9,9,9), 17),
age = c(rep("young", 9), rep("old", 8))
)
#plots
ggplot(data = controls, aes(strange_stories_ToM_mean, age)) +
geom_violin(
trim = FALSE,
alpha = 0.2,
draw_quantiles = c(0.25, 0.5, 0.75),
fill = "gray90"
) +
geom_point(
data = cases,
aes(colour = id, shape = id), # map color/shape to individual cases
size = 5,
show.legend = FALSE
) +
scale_shape_manual(values=c(16, 17, 15, 16, 17, 15)) +
scale_colour_manual(values=c("deeppink1","indianred3", "blueviolet", "springgreen3", "chartreuse2", "darkgreen")) +
scale_size_manual(values=c(5, 4, 5, 5, 4, 5)) +
theme_classic()
ggsave("strange_stories_ToM_mean.svg", width = 8, height = 8, units = "cm")
I looked at using 'for' and created a list to loop through (what I have is below) but I came unstuck at where the list should be incorporated when two data frames are being used and two plots...could lapply be best?
variables <- list() # Create empty listfor(i in ncol(FTD_data)) { # Using for-loop to add all columns tolist variables[[i]] <- FTD_data[ , i]}
names(variables) <- colnames(FTD_data) #rename list elements with variable names from df
for (i in variables)
{CODE TO PLOT INSERT HERE}

Answer 1

One approach to achieve your desired result would be to put your plotting code inside a function which takes one argument, the name of the column to plot. The only change I made to your plotting code is to replace the hardcoded strange_stories_ToM_mean by .data[[col]] to tell ggplot I want to plot the data column whose name is stored in col.
Also, instead of using a for loop I would recommend to use lapply when using ggplot2:
library(ggplot2)
plot_fun <- function(col) {
ggplot(data = controls, aes(.data[[col]], age)) +
geom_violin(
trim = FALSE,
alpha = 0.2,
draw_quantiles = c(0.25, 0.5, 0.75),
fill = "gray90"
) +
geom_point(
data = cases,
aes(colour = id, shape = id),
size = 5,
show.legend = FALSE
) +
scale_shape_manual(values=c(16, 17, 15, 16, 17, 15)) +
scale_colour_manual(values=c("deeppink1","indianred3", "blueviolet", "springgreen3", "chartreuse2", "darkgreen")) +
scale_size_manual(values=c(5, 4, 5, 5, 4, 5)) +
theme_classic()
}
cols_to_plot <- names(controls)[!names(controls) %in% c("id", "age")]
names(cols_to_plot) <- cols_to_plot
p <- lapply(cols_to_plot, plot_fun)
lapply(cols_to_plot, function(x) ggsave(paste0(x, ".svg"), plot = p[[x]], width = 8, height = 8, units = "cm"))
#> $strange_stories_ToM_mean
#> [1] "strange_stories_ToM_mean.svg"
#>
#> $strange_stories_ToM_median
#> [1] "strange_stories_ToM_median.svg"
p
#> $strange_stories_ToM_mean
#>
#> $strange_stories_ToM_median
DATA
set.seed(123)
cases <- data.frame(
id = factor(1:6),
strange_stories_ToM_mean = sample(6:8, 6, replace = TRUE),
strange_stories_ToM_median = sample(6:8, 6, replace = TRUE),
age = factor(c(rep("young", 3), rep("old", 3)))
)
controls <- data.frame(
id = 7:23,
strange_stories_ToM_mean = sample(c(6,6,7,7,7,7,7,7,7,8,8,8,9,9,9,9,9), 17),
strange_stories_ToM_median = sample(c(6,6,7,7,7,7,7,7,7,8,8,8,9,9,9,9,9), 17),
age = c(rep("young", 9), rep("old", 8))
)