4.1.1 Human

data <- read_excel(here(subdir, "data/PDGFRA_promoter_4C_human.xlsx"))

# Convert to long format so that we have three columns in the data frame:
# 1) Group (G34 or Other), 2) Average value, and 3) Standard deviation value
data_long <- data %>%
    unite(G34,   Average_G34_pGBMs,   stdeva_G34_pGBMs) %>%
    unite(Other, Average_Other_pGBMs, stdeva_other_pGBMs) %>%
    gather(Group, Value, G34, Other) %>%
    separate(Value, into = c("Average", "Stdev"), sep = "_")

# Convert the missing values around PDGFRA to 0
data_long$Average <- ifelse(data_long$Average == "NA", 0, data_long$Average)
data_long$Stdev   <- ifelse(is.na(data_long$Stdev),    0, data_long$Stdev)

# Make sure we have numeric columns for plotting
data_long$Average <- as.numeric(data_long$Average)
data_long$Stdev   <- as.numeric(data_long$Stdev)

# Colour palette
palette_human <- c("red", "navy")

# Write a plotting function
plot_4c <- function(df, palette) {
  
  df %>%
    rr_ggplot(aes(x = START, y = Average), plot_num = 1) +
    # Plot the stdev as an area "ribbon"
    geom_ribbon(aes(ymin = Average - Stdev, ymax = Average + Stdev, fill = Group), alpha = 0.3) +
    # Plot the solid line for the average
    geom_line(aes(colour = Group)) +
    # Set the colours
    scale_colour_manual(values = palette) +
    scale_fill_manual(values = palette) +
    # Add more breaks to the x-axis
    scale_x_continuous(breaks = seq(from = min(data$START), to = max(data$START), by = 20000)) +
    theme_cowplot() +
    theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = rel(0.7)))
  
}

plot_4c(data_long, palette_human)

## Loading required package: readr

_{[figure/source data @ G34-gliomas/bulk_transcriptome_epigenome/figures/05//human_pdgfra_plot…]}

4.1.2 Mouse

data <- read_excel(here(subdir, "data/PDGFRA_promoter_4C_mice.xlsx"))

# Convert to long format so that we have three columns in the data frame:
# 1) Group (G34 or Other), 2) Average value, and 3) Standard deviation value
data_long <- data %>%
  unite(GE,     Average_GE, STDEVA_GE) %>%
  unite(Cortex, Average_Cortex, STDEVA_Cortex) %>%
  unite(ESC,    Average_ESC, STDEVA_ESC) %>%
  gather(Group, Value, GE, Cortex, ESC) %>%
  separate(Value, into = c("Average", "Stdev"), sep = "_")

# Make sure we have numeric columns for plotting
data_long$Average <- as.numeric(data_long$Average)
data_long$Stdev   <- as.numeric(data_long$Stdev)

# Colour palette
palette_mouse <- c("blue", "orange", "gray50")

# Plot
plot_4c(data_long, palette_mouse)

_{[figure/source data @ G34-gliomas/bulk_transcriptome_epigenome/figures/05//mouse_pdgfra_plot…]}

4.2.1 Human

data <- read_excel(here(subdir, "data/GSX2_promoter_4C_human.xlsx"))

# Convert to long format so that we have three columns in the data frame:
# 1) Group (G34 or Other), 2) Average value, and 3) Standard deviation value
data_long <- data %>%
    unite(G34,   Average_G34, STDEVA_G34) %>%
    unite(Other, Average_other_pGBMs, STDEVA_non_G34) %>%
    gather(Group, Value, G34, Other) %>%
    separate(Value, into = c("Average", "Stdev"), sep = "_")

# Make sure we have numeric columns for plotting
data_long$Average <- as.numeric(data_long$Average)
data_long$Stdev   <- as.numeric(data_long$Stdev)

plot_4c(data_long, palette_human)

_{[figure/source data @ G34-gliomas/bulk_transcriptome_epigenome/figures/05//human_gsx2_plot…]}

4.2.2 Mouse

data <- read_excel(here(subdir, "data/GSX2_promoter_4C_mice.xlsx"))

# Convert to long format so that we have three columns in the data frame:
# 1) Group (G34 or Other), 2) Average value, and 3) Standard deviation value
data_long <- data %>%
  unite(GE,     Average_GE, STDEVA_GE) %>%
  unite(Cortex, Average_Cortex, STDEVA_Cortex) %>%
  unite(ESC,    Average_ESC, STDEVA_ESC) %>%
  gather(Group, Value, GE, Cortex, ESC) %>%
  separate(Value, into = c("Average", "Stdev"), sep = "_") %>% 
  filter(Group != "ESC")

# Make sure we have numeric columns for plotting
data_long$Average <- as.numeric(data_long$Average)
data_long$Stdev   <- as.numeric(data_long$Stdev)

plot_4c(data_long, palette_mouse)

_{[figure/source data @ G34-gliomas/bulk_transcriptome_epigenome/figures/05//mouse_gsx2_plot…]}