R/run_kea.R

In kalganem/creedenzymatic: creedenzymatic

#' Run KEA3 API based on a set of gene symbols
#'
#' This function takes in HGNC gene symbols and connect to KEA3 API and returns results
#'
#' @param gene_set vector, HGNC gene symbols based on the differentially phosphorylated peptides
#' @param lib searched kea libraries "kinase-substrate" or "all" (default is "kinase-substrate" which will return only kinase libraries like ChengKSIN, PTMsigDB, PhosDAll)
#'
#' @return list, tables from each KEA3 library
#'
#' @export
#'
#'
#'

run_kea <- function(gene_set, lib = "kinase-substrate") {

  rbind(stk_pamchip_87102_mapping, ptk_pamchip_86402_mapping) %>%
    dplyr::filter(ID %in% gene_set)

  url <- "https://amp.pharm.mssm.edu/kea3/api/enrich/"

  response <-  httr::POST(url = url, body = list(gene_set = gene_set), encode = "json")

  if (response$status_code == 200) {

    json <-  httr::content(response, "text")
    results <-  jsonlite::fromJSON(json)

    if(lib == "kinase-substrate") {
      results <- results[names(results) %in% c("PTMsigDB", "ChengKSIN", "PhosDAll")]

      purrr::map_df(results, base::rbind) %>%
        dplyr::select(TF, Rank) %>%
        dplyr::mutate(Rank = as.numeric(Rank)) %>%
        dplyr::group_by(TF) %>%
        dplyr::summarise(Score = mean(Rank)) %>%
        dplyr::ungroup() -> integrated_results_df

      results$`Integrated--meanRank` <- integrated_results_df

      results

    }

    else {
      results
    }


  }
  else {
    message("Couldn't connect to KEA3 API successfully")
    return(NA_real_)
    }


}