ggplot with p-values

library(ggplot2)
library(ggpubr)

setwd("/home/bio0/00-NGS/SETDB1_TCGA")

dta <- read.csv("exp.LUNG.FPKM.EpiStem.ggplot.2.csv", header = F)
colnames(dta) <- c("Gene","Symbol","Sample","FPKM","Group")
names(dta)

dta2 <-  dta[grep("DNMT1", dta$Symbol), ]
dta2$Group<-factor(dta2$Group, levels = c("Gain.Tumor",
                                          "Dipl.Tumor",
                                          "Dipl.Normal",
                                          "Loss.Tumor"))

my_comparisons <- list(c("Gain.Tumor","Dipl.Tumor"),
                       c("Dipl.Tumor","Dipl.Normal"),
                       c("Loss.Tumor","Dipl.Normal"),
                       c("Gain.Tumor","Dipl.Normal"),
                       c("Gain.Tumor","Loss.Tumor"),
                       c("Loss.Tumor","Dipl.Tumor"))

q <- ggplot(dta2, aes(x=Group,y=log10(1+FPKM),group=Group))
q + geom_jitter(alpha=0.6,width=0.3, aes(fill=Gene)) + ggtitle("DNMT1") +
  geom_violin(alpha=0.6,scale="width",aes(fill=Group)) + 
  #geom_boxplot(width=.5, outlier.shape = NA) +
  stat_compare_means(comparisons = my_comparisons) + guides(fill=FALSE)