leafcutter result exploratory analysis

leafcutter_ea.R

library(tidyverse)
library(ggrepel)

# load the data to variable x
x <- read_csv('leafcutter_junctions.csv')

x %>% 
 # filters the dataframe to keep only significant called junctions
 filter(abs(deltapsi) > 0.1 & p.adjust < 0.05) %>% 
 # groups junctions by comparison
 group_by(comparison) %>%
 # show the counts of genes or introns per group
 summarise(
   genes = n_distinct(genes),
   events = n_distinct(intron))

# this plots a generic/bad volcano plot
p <- x %>% 
  ggplot(aes(deltapsi, -log10(p.adjust))) +
  geom_point() 

# show the plot
p

# break it down by comparison
p  + facet_wrap(vars(comparison))