Combining two heatmaps with the variables next to each other-CodePudding

I'm trying to combine two heatmaps. I want var_a and var_x on the y axis with for example: var_a first and then var_x. I don't know if I should do this by changing the dataframe or combining them, or if I can do this in ggplot.

Below I have some example code and a drawing of what I want (since I don't know if I explained it right).

I hope someone has ideas how I can do this either in the dataframe or in ggplot!

Example code:

df_one <- data.frame(
        vars = c("var_a", "var_b", "var_c"),
        corresponding_vars = c("var_x", "var_y", "var_z"),
        expression_organ_1_vars = c(5, 10, 20),
        expression_organ_2_vars = c(50, 2, 10),
        expression_organ_3_vars = c(5, 10, 3)
        )

df_one_long <- pivot_longer(df_one, 
                                cols=3:5, 
                                names_to = "tissueType", 
                                values_to = "Expression")

expression.df_one <- ggplot(df_one_long,
                            mapping = aes(y=tissueType, x=vars, fill = Expression))  
                                geom_tile()
expression.df_one


df_two <- data.frame(
        corresponding_vars = c("var_x", "var_y", "var_z"),
        expression_organ_1_corresponding_vars = c(100, 320, 120),
        expression_organ_2_corresponding_vars = c(23, 30, 150),
        expression_organ_3_corresponding_vars = c(89, 7, 200)
        )

df_two_long <- pivot_longer(df_one, 
                                cols=3:5, 
                                names_to = "tissueType", 
                                values_to = "Expression")

expression.df_two <- ggplot(df_two_long,
                            mapping = aes(y=tissueType, x=vars, fill = Expression))  
                                geom_tile()
expression.df_two

Drawing:

CodePudding user response：

You can bind your data frames together and pivot into a longer format so that vars and corresponding vars are in the same column, but retain a grouping variable to facet by:

df_two %>%
  mutate(cor = corresponding_vars) %>%
  rename_with(~sub('corresponding_', '', .x)) %>%
  bind_rows(df_one %>% rename(cor = corresponding_vars)) %>%
  pivot_longer(contains('expression'), names_to = 'organ') %>%
  mutate(organ = gsub('expression_|_vars', '', organ)) %>%
  group_by(cor) %>%
  summarize(vars = vars, organ = organ, value = value,
            cor = paste(sort(unique(vars)), collapse = ' cor ')) %>%
  ggplot(aes(vars, organ, fill = value))  
  geom_tile(color = 'white', linewidth = 1)  
  facet_grid(.~cor, scales = 'free_x', switch = 'x')  
  scale_fill_viridis_c()  
  coord_cartesian(clip = 'off')  
  scale_x_discrete(expand = c(0, 0))  
  theme_minimal(base_size = 16)  
  theme(strip.placement = 'outside',
        axis.text.x = element_blank(),
        axis.ticks.x.bottom = element_line(),
        panel.spacing.x = unit(3, 'mm'))

CodePudding user response：

Okay, so I solved the issue for my own project, which is to convert it to a scatter plot. I combined both datasets and then used a simple scatterplot.

df.combined <- dplyr::full_join(df_two_long, df_one_long, 
   by = c("vars", "corresponding_vars", "tissueType"))

ggplot(df.combined, 
   aes(x=vars, y=tissueType, colour=Expression.x, size = Expression.y))   
   geom_point()

It's not a solution with heatmaps, but I don't know how to do that at the moment.