Question about the dots on Quartile groups in boxplot

Question

I have Microarray Normalized Expression data for a specific Gene. It looks like below in a dataframe B

SampleID    Gene    Type
Sample1     5.02    Tumor
Sample2     5.06    Tumor
Sample3     5.1     Tumor
Sample4     5.11    Tumor
Sample5    5.127    Normal
Sample6     5.12    Normal
Sample7    5.138    Normal
Sample8    5.149    Normal

I see that the minimum expression value in the table is 5.0 and maximum expression value is around 5.9.

I wanted to show the expression between two conditions with a boxplot and used following code.

q <- ggboxplot(B, x = "Type", y = "Gene",
               color = "black", palette = "npg",
               add = "jitter", ylab = 'Gene expression', xlab=FALSE,
               order=c("Normal", "Tumor"))
q + stat_compare_means(method = "t.test") + 
  geom_point() + 
  stat_n_text()

This gave a plot like this

But when I remove the jitter from the code,

q <- ggboxplot(B, x = "Type", y = "Gene",
               color = "black", palette = "npg",
               ylab = 'Gene expression', xlab=FALSE,
               order=c("Normal", "Tumor"))
q + stat_compare_means(method = "t.test") + 
  geom_point() + 
  stat_n_text()

I see many black dots in the middle of the boxplot like this

May I know why I see those dots in the second boxplot after removing the jitter. Is there a way to avoid that?

Answer 1

You add the points with geom_point(). Just remove it and you will get your "empty" boxplot.

q <- ggboxplot(B, x = "Type", y = "Gene",
               color = "black", palette = "npg",
               ylab = 'Gene expression', xlab=FALSE,
               order=c("Normal", "Tumor"))

Unfortunately I couldn't use stat_compare_means(method = "t.test") and stat_n_text(), but this two just add the labels.