02-deg_visualization.Rmd

# Differentially Expressed Genes

These are visualizations of the differentially expressed genes (DEGs).

## Shared DEGs
```{r}
#Input: named list of DEG tables
combined_deg_heatmap <- function(X, num_genes = 50) {
  combined_degs <- X %>%
    map(
      ~ filter(., pvalue <= 0.05) %>%
        arrange(desc(abs(log2FoldChange))) %>%
        slice_head(n = num_genes) %>%
        pull(Symbol)
    ) %>%
    flatten_chr() %>%
    unique()
  
  mat <- X %>%
    map( ~ filter(., Symbol %in% combined_degs) %>%
           select(Symbol, log2FoldChange)) %>%
    bind_rows(.id = "Group") %>%
    pivot_wider(names_from = Group, values_from = log2FoldChange) %>%
    column_to_rownames(var = "Symbol") %>%
    drop_na() %>%
    as.matrix()
  
  min = min(mat, na.rm = T)
  max = max(mat, na.rm = T)
  
  lgd = ComplexHeatmap::Legend(
    title = "log2FC",
    col_fun = circlize::colorRamp2(c(min, 0, max), c("blue", "white", "red")),
    at = c(min, 0, max),
    labels = c(round(min, 2), 0, round(max, 2)),
    direction = "vertical",
    labels_gp = grid::gpar(fontsize = 8),
    title_gp = grid::gpar(fontsize = 8)
  )
  
  ht = ComplexHeatmap::Heatmap(
    mat,
    column_names_rot = 0,
    column_names_gp = grid::gpar(fontsize = 8),
    column_names_centered = TRUE,
    row_names_gp = grid::gpar(fontsize = 4),
    show_row_names = TRUE,
    show_row_dend = FALSE,
    show_heatmap_legend = FALSE
  )
  
  ComplexHeatmap::draw(
    ht,
    padding = unit(c(2, 2, 2, 2), "mm"),
    heatmap_legend_list = lgd,
    heatmap_legend_side = "right"
  )
  
}

global_state$data %>%
  map("data") %>%
  combined_deg_heatmap()
```

## Volcano Plots
```{r, results='asis'}
#Input: DEG table
volcano_plot <- function(X) {
  top10 <- X %>%
    filter(pvalue <= 0.05) %>%
    arrange(desc(abs(log2FoldChange))) %>%
    slice_head(n = 10) %>%
    pull(Symbol)
  
  #label
  ns <- paste0("NS (", sum(X$pvalue > 0.05), ")")
  up <-
    paste0("Up (", sum(X$pvalue <= 0.05 & X$log2FoldChange > 0), ")")
  down <-
    paste0("Down (", sum(X$pvalue <= 0.05 &
                           X$log2FoldChange < 0), ")")
  
  plot <- X %>%
    mutate(
      Significant = case_when(
        pvalue > 0.05 ~ "NS",
        pvalue <= 0.05 & log2FoldChange >= 0 ~ "Up",
        pvalue <= 0.05 & log2FoldChange < 0 ~ "Down"
      ) %>% as.factor(),
      top10label = if_else(Symbol %in% top10, Symbol, NA_character_)
    ) %>%
    ggplot(aes(
      x = log2FoldChange,
      y = -log10(pvalue),
      col = Significant,
      label = top10label
    )) +
    geom_point() +
    scale_color_manual(labels = c(down, ns, up),
                       values = c("blue", "black", "red")) +
    geom_text_repel() +
    geom_hline(linetype='dotted', yintercept = -log10(0.05), col = "black") +
    theme_pubr()
  return(plot)
}

global_state$data %>%
  map( ~ knit_child(
    text = c(
      '',
      '### `r .$name`',
      '',
      '```{r}',
      'volcano_plot(.$data)',
      '```',
      ''
    ),
    envir = environment(),
    quiet = TRUE
  )) %>%
  list_c() %>%
  cat(sep = "\n")
```

<!-- ## Expression of Top DEGs -->
```{r, results='asis'}
#Input: globalstate$data list element
group_count_heatmap <- function(X) {
  data <- X$data
  
  lower <- round(quantile(data$log2FoldChange, 0.10), 3)
  upper <- round(quantile(data$log2FoldChange, 0.90), 3)
  
  filtered <- data %>%
    filter(pvalue <= 0.05, log2FoldChange >= upper | log2FoldChange <= lower) %>%
    pull(Symbol)
  
  group_design <- global_state$design %>%
    filter(Group %in% c(X$group1, X$group2))
  
  mat <- global_state$counts %>%
    select(Symbol, group_design %>% pull(Sample)) %>%
    filter(Symbol %in% filtered) %>%
    column_to_rownames(var = "Symbol") %>%
    as.matrix()
  
  mat = t(scale(t(mat)))
  
  row_order = seriate(dist(mat), method = "TSP") %>% get_order()
  
  min = min(mat, na.rm = T)
  max = max(mat, na.rm = T)
  
  lgd = ComplexHeatmap::Legend(
    title = NULL,
    col_fun = circlize::colorRamp2(c(min, 0, max), c("blue", "white", "red")),
    at = c(min, 0, max),
    labels = c(round(min, 2), 0, round(max, 2)),
    direction = "vertical",
    labels_gp = grid::gpar(fontsize = 8)
  )
    
  group_data = group_design$Group %>% as.factor()
  
  group_cols = distinctColorPalette(k = nlevels(group_data)) %>% set_names(levels(group_data))
  
  annotation = ComplexHeatmap::HeatmapAnnotation(
    Group = group_data,
    show_annotation_name = F,
    col = list(Group = group_cols),
    annotation_legend_param = list(
      Group = list(
        color_bar = "discrete",
        title = NULL,
        direction = "horizontal",
        title_position = "topcenter",
        title_gp = grid::gpar(fontsize = 8),
        labels_gp = grid::gpar(fontsize = 8),
        nrow = 1
      )
    )
  )
  
  ht = ComplexHeatmap::Heatmap(
    mat,
    row_order = row_order,
    top_annotation = annotation,
    column_names_rot = 45,
    column_names_gp = grid::gpar(fontsize = 8),
    show_row_names = FALSE,
    show_row_dend = FALSE,
    show_heatmap_legend = FALSE
  )
  
  ComplexHeatmap::draw(
    ht,
    padding = unit(c(2, 15, 2, 2), "mm"),
    heatmap_legend_list = lgd,
    heatmap_legend_side = "right",
    annotation_legend_side = "top"
  )

}

if(global_state$using_counts) {
  global_state$data %>%
    map( ~ knitr::knit_child(
      text = c(
        '',
        '### `r .$name`',
        '',
        '```{r}',
        'group_count_heatmap(.)',
        '```',
        ''
      ),
      envir = environment(),
      quiet = TRUE
    )) %>%
    c("\n\n## Expression of Top DEGs\n\n", .) %>%
    list_c() %>%
    cat(sep = "\n")
}
```