analysis/scripts/figures/colocalization_supp.R

In BCMSLab/rkip: Gene co-expression analysis of RKIP, autophagy and EMT in prostate cancer

# load libraries
library(tidyverse)
library(reshape2)
library(ggimage)
library(cowplot)

# load data
if(!file.exists('data/image_supp.png')) {
  download.file('https://ndownloader.figshare.com/files/12556949',
                destfile = 'data/image_supp.png')
}

g1 <- data_frame(image = 'data/image_supp.png') %>%
  ggplot() +
  geom_image(aes(x = .5, y = .5, image = image), size = Inf) +
  scale_x_continuous(breaks = c(0.125, 0.375, 0.625, 0.875),
                     labels = c('', 'RKIP', 'Hoechst', 'Merged'),
                     position = 'top',
                     name = NULL) +
  scale_y_continuous(breaks = c(.17, .5, .82),
                     labels = c('NF1', 'PARK7', 'CTNNB1'),
                     name = NULL) +
  theme(axis.ticks = element_blank(),
        axis.text = element_text(size = 9),
        axis.line = element_blank())

if(!file.exists('data/coloc_supp.csv')) {
  download.file('https://ndownloader.figshare.com/files/12302144',
                destfile = 'data/coloc_supp.csv')
}

df <- read_csv('data/coloc_supp.csv') %>%
  setNames(c('symbol', "Pearson's", "Manders (M1)", "Manders (M2)"))

g2 <- df %>%
  gather(type, value, -symbol) %>%
  ggplot(aes(x = symbol, y = value)) +
  geom_jitter(width = .3, alpha = .5) +
  geom_point(data = df %>%
               gather(type, value, -symbol) %>%
               group_by(symbol, type) %>%
               summarise(ave = mean(value)),
             aes(y = ave),
             color = 'red',
             width = .3) +
  geom_errorbar(data = df %>%
                  gather(type, value, -symbol) %>%
                  group_by(symbol, type) %>%
                  summarise(ave = mean(value),
                            sd = sd(value),
                            upper = ave + sd,
                            lower = ave - sd),
                aes(y = ave, ymin = lower, ymax = upper),
                color = 'red',
                width = .3) +
  facet_wrap(~type, nrow = 1) +
  lims(y = c(0,1.05)) +
  labs(y = 'Coefficient Value\n', x = '') +
  theme_bw() +
  theme(axis.text.x = element_text(size = 9))

plot_grid(g1, g2,
          ncol = 1,
          labels = 'AUTO',
          label_fontface = 'plain',
          label_size = 10,
          scale = .95) %>%
  ggsave(plot = .,
         filename = 'manuscript/figures/colocalization_supp.png',
         width = 18, height = 18, units = 'cm')