#' Plot gene aggregate plot
 #'
 #' @param genes a character vector of genes to include in aggregate plot, if NULL then all genes are used.
 #' @inheritParams plot_agg_regions
 #'
 #' @return a ggplot object containing the aggregate methylation trend of genes.
 #'
 #' @examples
 #' nmr <- load_example_nanomethresult()
 #' plot_agg_genes(nmr)
 #'
 plot_agg_genes <- function(
     x,
     genes = NULL,
     binary_threshold = 0.5,
     group_col = NULL,
     flank = 2000,
     stranded = TRUE,
     span = 0.05,
     palette = ggplot2::scale_colour_brewer(palette = "Set1")
 ) {
     gene_regions <- exons_to_genes(exons(x))
     if (!is.null(genes)) {
         gene_regions <- gene_regions %>%
             filter(.data$symbol %in% genes)
     }
 
     plot_agg_regions(
         x,
         regions = gene_regions,
         binary_threshold = binary_threshold,
         group_col = group_col,
         flank = flank,
         stranded = stranded,
         span = span,
         palette = palette
     )
 }
 
 plot_agg_tss <- function(
     x,
     genes = NULL,
     binary_threshold = 0.5,
     group_col = NULL,
     flank = 2000,
     stranded = TRUE,
     span = 0.05,
     palette = ggplot2::scale_colour_brewer(palette = "Set1")
 ) {
     gene_regions <- exons_to_genes(exons(x))
     if (!is.null(genes)) {
         gene_regions <- gene_regions %>%
             filter(.data$symbol %in% genes)
     }
     tss_regions <- gene_regions %>%
         mutate(
             start = case_when(
                 strand == "+" ~ start,
                 strand == "-" ~ end,
                 TRUE ~ start)
         ) %>%
         mutate(
             start = start - flank,
             end = start + 2*flank
         )
     kb_marker <- round(flank / 1000, 1)
     labels <- c(
         glue::glue("-{kb_marker}kb"),
         "TSS",
         glue::glue("+{kb_marker}kb")
     )
 
     p <- plot_agg_regions(
         x,
         regions = tss_regions,
         binary_threshold = binary_threshold,
         group_col = group_col,
         flank = 0,
         stranded = stranded,
         span = span,
         palette = palette
     )
     # hack to delete existing to avoid warning
     p$scales$scales[[which(p$scales$find("x"))]] <- NULL
 
     p + ggplot2::scale_x_continuous(
         name = glue::glue(""),
         breaks = c(0, 0.5, 1),
         limits = c(0, 1),
         labels = labels
     )
 }
 
 plot_agg_tes <- function(
     x,
     genes = NULL,
     binary_threshold = 0.5,
     group_col = NULL,
     flank = 2000,
     stranded = TRUE,
     span = 0.05,
     palette = ggplot2::scale_colour_brewer(palette = "Set1")
 ) {
     gene_regions <- exons_to_genes(exons(x))
     if (!is.null(genes)) {
         gene_regions <- gene_regions %>%
             filter(.data$symbol %in% genes)
     }
     tes_regions <- gene_regions %>%
         mutate(
             start = case_when(
                 strand == "+" ~ end,
                 strand == "-" ~ start,

                 TRUE ~ end)

         ) %>%
         mutate(
             start = start - flank,
             end = start + 2*flank
         )
     kb_marker <- round(flank / 1000, 1)
     labels <- c(
         glue::glue("-{kb_marker}kb"),
         "TES",
         glue::glue("+{kb_marker}kb")
     )
 
     p <- plot_agg_regions(
         x,
         regions = tes_regions,
         binary_threshold = binary_threshold,
         group_col = group_col,
         flank = 0,
         stranded = stranded,
         span = span,
         palette = palette
     )
     # hack to delete existing to avoid warning
     p$scales$scales[[which(p$scales$find("x"))]] <- NULL
 
     p + ggplot2::scale_x_continuous(
         name = glue::glue(""),
         breaks = c(0, 0.5, 1),
         limits = c(0, 1),
         labels = labels
     )
 }