R/manhattan_plot_per_area.R

In drake69/semseeker: Stochastic Epigenetic Mutations SEM Seeker

#' Title
#'
#' @param marker investigated marker eg. MUTATIONS, DELTAR, DELTAQ
#' @param figure HYPO, HYPER
#' @param group genomic area (eg. GENE, ISLAND, DMR)
#' @param subgroup sub genomic area (TSS1550), depending on the genomic area
#' @param family fullname of the family used for the association analysis
#' @param adjust_method colnames of the pvalue adjusted to use
#' @param phenotype variable to select from the sample_sheet to use for coloring point
#' @param only_significant_areas TRUE if filter for pvalue < 0.05
#'
#' @export
#'
manhattan_plot_per_area <- function(marker,figure,group,subgroup,family, adjust_method,phenotype, only_significant_areas=FALSE){

  if(only_significant_areas)
  {
    # get inference file

    # select for family, marker and figure, adjust_method, group and subgroup
  }

  pivot_data <- pivot_to_long_format(marker, figure, group,subgroup)

  group_variable <- pivot_data[,group]

  ggplot2::ggplot(pivot_data, ggplot2::aes(x = factor(group_variable), y = ifelse(pivot_data$VALUE < 0, 0, pivot_data$VALUE), fill = phenotype)) +
    ggplot2::geom_point(shape = 21, position = ggplot2::position_jitter(), alpha = 0.7, color = as.numeric(pivot_data[,group])) +
    ggplot2::labs(x = group, y = "VALUE", title = paste("Outlier per ",group)) +
    ggplot2::scale_fill_gradient(low = "white", high = "blue") +
    ggplot2::labs(title = paste(marker, " per ", group), x = group, y = marker) +
    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5))

}