R/olink_Pathway_Visualization.R

In OlinkAnalyze: Facilitate Analysis of Proteomic Data from Olink

#' Creates bargraph of top/selected enrichment terms from GSEA or ORA results from olink_pathway_enrichment()
#' 
#' Pathways are ordered by increasing p-value (unadjusted)
#'
#'@param enrich_results data frame of enrichment results from olink_pathway_enrichment()
#'@param method method used in olink_pathway_enrichment ("GSEA" (default) or "ORA")
#'@param keyword (optional) keyword to filter enrichment results on, if not specified, displays top terms
#'@param number_of_terms number of terms to display, default is 20
#'@return A bargraph as a ggplot object
#'@examples
#'\donttest{
#'library(dplyr)
#'# Run olink_ttest or other stats test (see documentaiton )
#'npx_df <- npx_data1 %>% filter(!grepl('control',SampleID, ignore.case = TRUE))
#'ttest_results <- olink_ttest(df=npx_df,
#'                              variable = 'Treatment',
#'                              alternative = 'two.sided')
#'
#' try({ # This expression might fail if dependencies are not installed
#'# Run olink_pathway_enrichment (see documentation)
#' gsea_results <- olink_pathway_enrichment(data = npx_data1, test_results = ttest_results)
#' ora_results <- olink_pathway_enrichment(data = npx_data1,
#'                                        test_results = ttest_results, method = "ORA")
#'olink_pathway_visualization(enrich_results = gsea_results)
#'olink_pathway_visualization(enrich_results = gsea_results, keyword = "immune")
#'olink_pathway_visualization(enrich_results = ora_results, method = "ORA", number_of_terms = 15)
#'})
#'
#'}
#'
#' @seealso \itemize{
#' \item{\code{\link[OlinkAnalyze:olink_pathway_enrichment]{olink_pathway_enrichment}} for generating enrichment results}
#' \item{\code{\link[OlinkAnalyze:olink_pathway_heatmap]{olink_pathway_heatmap}} for generating a heat map of results}
#' }
#'
#'@importFrom dplyr filter arrange slice_head mutate desc 
#'@importFrom ggplot2 ggplot geom_bar geom_text aes coord_flip xlab
#'@importFrom stringr str_trunc
#'@importFrom forcats fct_inorder
#'@importFrom magrittr %>%
#'@export

olink_pathway_visualization <- function(enrich_results, method = "GSEA", keyword = NULL, number_of_terms = 20) {
  if (!(method %in% c("ORA", "GSEA"))) {
    stop("Method must be \"GSEA\" or \"ORA\".")
  }
  
  if(!is.null(keyword)) {
    enrich_results <- enrich_results %>%
      dplyr::filter(grepl(pattern = toupper(keyword), x = Description))
    
    if (nrow(enrich_results) == 0) {
      stop("Keyword not found. Please choose a different keyword or use a set number of terms.")
    }
  }
  
  enrich_results <- enrich_results %>% 
    dplyr::arrange(pvalue) %>%
    dplyr::slice_head(n = number_of_terms) %>%
    dplyr::arrange(dplyr::desc(x = pvalue)) %>%
    dplyr::mutate(Description = stringr::str_trunc(string = Description, width = 50, side = "center")) %>% 
    dplyr::mutate(Description = forcats::fct_inorder(f = Description))
  
  if (method == "ORA") {
    p <- ggplot2::ggplot(data = enrich_results, ggplot2::aes(x = Description, y = Count))
  } else if (method == "GSEA") {
    p <- ggplot2::ggplot(data = enrich_results, ggplot2::aes(x = Description, y = NES))
  }
  
  p <- p +
    ggplot2::geom_bar(stat = "identity", ggplot2::aes(fill = p.adjust)) +
    OlinkAnalyze::olink_fill_gradient(coloroption = c('teal', 'red')) +
    ggplot2::coord_flip() +
    ggplot2::xlab("Description")
  
  if (method == "ORA") {
    p <- p +
      ggplot2::geom_text(ggplot2::aes(label = paste(gsub(x = GeneRatio, pattern = "/.*", replacement = ""),
                                                    gsub(x = BgRatio, pattern = "/.*", replacement = ""), sep = "/")),
                         hjust = -0.1, color = "black", size = 3.5)
  }
  
  return(p)
}