#' run_gsea
#'
#' Function to run gene set enrichment analysis and plot a GSEA plot.
#'
#' @param hits A data.frame containing the genes id, a score value and preferably a treatment column but not necessary.
#' @param gene_column The name of the column that contains the genes. Default is 'Gene'.
#' @param score_column The name of the column that contains the score values. Default is 'IS'.
#' @param treatment_column The name of the column that contains the treatments. Default is NULL.
#' @param treatment The name of the treatment you want to keep. Default is NULL.
#' @param species Specify the species. Currently, only 'human' and 'mouse' are available.
#' @param pos_enrichment Logical to tell if you want to only look at positive enrichment score.
#' If FALSE, show only negative.
#' @param pval_cutoff The p-value cutoff for the enrichment analysis.
#' @param minGSSize minimal size of each gene set for analyzing. default here is 3
#' @param database Specify the database. Currently, WikiPathway, KEGG, GO and CETSA are available.
#'
#' @return A list that contains the results and the plot.
#'
#' @export
#'
#' @seealso \code{\link{clusterProfiler}}
run_gsea <- function(hits, gene_column = "Gene", score_column = "IS",
treatment_column = NULL, treatment = NULL,
species = c("human", "mouse"), pos_enrichment = TRUE,
pval_cutoff = 0.01, minGSSize = 3,
database = c("WikiPathway", "KEGG", "GO", "CETSA")){
require(clusterProfiler)
species <- tolower(species)
species <- match.arg(species)
database <- match.arg(database)
if(!("KEGGREST" %in% installed.packages())){
message("Installing KEGGREST package")
BiocManager::install("KEGGREST")
}
if(species == "human"){
if(!("org.Hs.eg.db" %in% installed.packages())){
message("Installing org.Hs.eg.db package")
BiocManager::install("org.Hs.eg.db")
}
}
else if(species == "mouse"){
if(!("org.Mm.eg.db" %in% installed.packages())){
message("Installing org.Mm.eg.db package")
BiocManager::install("org.Mm.eg.db")
}
}
org_data <- ifelse(species == "human", "org.Hs.eg.db", "org.Mm.eg.db")
if(!is.null(treatment_column) & !is.null(treatment)){
hits <- hits[which(hits[[treatment_column]] == treatment),]
}
if(any(is.na(hits[[score_column]]))){
hits <- hits[which(!is.na(hits[[score_column]])),]
}
if(any(is.na(hits[[gene_column]]))){
hits <- hits[which(!is.na(hits[[gene_column]])),]
}
if(database != "CETSA"){
### convert gene IDs
hits_gene_id <- clusterProfiler::bitr(unique(sort(hits[[gene_column]])),
fromType = "SYMBOL", toType = c("ENTREZID"),
OrgDb = org_data, drop = FALSE)
colnames(hits_gene_id) <- c(gene_column, "Gene_id")
hits <- dplyr::left_join(hits, hits_gene_id, by = gene_column, multiple = "all")
if(any(is.na(hits$Gene_id))){
hits <- hits[which(!is.na(hits$Gene_id)),]
}
}
else{
hits$Gene_id <- hits[[gene_column]]
}
hits$score <- hits[[score_column]]
hits <- hits[, c("Gene_id", "score")]
if(any(duplicated(hits$Gene_id))){
hits <- hits[-which(duplicated(hits$Gene_id)),]
}
hits <- hits[order(hits$score, decreasing = TRUE),]
hits <- as.data.frame(hits)
rownames(hits) <- hits$Gene_id
hits$Gene_id <- NULL
hits <- unlist(as.list(as.data.frame(t(hits))))
if(database == "WikiPathway"){
wp <- get_wikipath(species = species) # wiki pathway
gsea_res <- clusterProfiler::GSEA(hits,
TERM2GENE=wp[,c("wpid", "gene")],
TERM2NAME=wp[,c("wpid", "name")],
scoreType = "pos", pvalueCutoff = pval_cutoff,
minGSSize = minGSSize)
}
else if(database == "KEGG"){
if(species == "human"){
gsea_res <- clusterProfiler::gseKEGG(hits, organism = "hsa", pvalueCutoff = pval_cutoff,
minGSSize = minGSSize)
}
else if(species == "mouse"){
gsea_res <- clusterProfiler::gseKEGG(hits, organism = "mmu", pvalueCutoff = pval_cutoff,
minGSSize = minGSSize)
}
rm(.KEGG_clusterProfiler_Env, envir=sys.frame()) # hidden object from clusterprofiler prevent dbplyr to load when in the environment
}
else if(database == "GO"){
if(species == "human"){
gsea_res <- clusterProfiler::gseGO(hits, OrgDb = "org.Hs.eg.db", pvalueCutoff = pval_cutoff,
ont = "BP", minGSSize = minGSSize)
}
else if(species == "mouse"){
gsea_res <- clusterProfiler::gseGO(hits, OrgDb = "org.Mm.eg.db", pvalueCutoff = pval_cutoff,
ont = "BP", minGSSize = minGSSize)
}
rm(.GO_clusterProfiler_Env, .GOTERM_Env, envir=sys.frame()) # hidden object from clusterprofiler prevent dbplyr to load when in the environment
}
else if(database == "CETSA"){
gsea_res <- clusterProfiler::GSEA(hits,
TERM2GENE=cetsa_gsea_database[,c("cetsa.id", "gene")],
TERM2NAME=cetsa_gsea_database[,c("cetsa.id", "name")],
scoreType = "pos", pvalueCutoff = pval_cutoff,
minGSSize = minGSSize)
}
if(nrow(gsea_res@result) == 0){
#no term enriched under specific pvalueCutoff...
graph <- ggplot(data.frame(x = c(0,1), y = c(0,1)), aes(x,y, label = "s")) +
geom_text(x=0.5, y=0.5, label = paste("No term enriched \nunder p-value of", pval_cutoff), size = 10) +
cowplot::theme_cowplot() +
theme(axis.text.x = element_blank(),
axis.title.x = element_blank(),
axis.ticks.x = element_blank(),
axis.text.y = element_blank(),
axis.title.y = element_blank(),
axis.ticks.y = element_blank())
return(list("res" = NULL, "graph" = graph))
}
else{
res <- gsea_res@result
if(database != "CETSA"){
res$geneSymbol <- unlist(lapply(strsplit(res$core_enrichment, "/"),
function(x){x <- as.numeric(x)
g <- hits_gene_id[[gene_column]][which(!is.na(match(hits_gene_id$Gene_id, x)))]
g <- paste(g, collapse = "/");
g
}
)
)
}
else{
extra_info <- unique(cetsa_gsea_database[,c("cetsa.id", "function", "functional.hypothesis")])
colnames(extra_info)[1] <- "ID"
res <- dplyr::left_join(res, extra_info, by = "ID")
}
if(pos_enrichment){
if(length(which(gsea_res@result$enrichmentScore > 0))){
graph <- enrichplot::gseaplot2(gsea_res,
geneSetID = which(gsea_res@result$enrichmentScore > 0))
}
else{
message("All enrichment score are negative, showing those instead.")
graph <- enrichplot::gseaplot2(gsea_res,
geneSetID = which(gsea_res@result$enrichmentScore < 0))
}
}
else{
if(length(which(gsea_res@result$enrichmentScore < 0))){
graph <- enrichplot::gseaplot2(gsea_res,
geneSetID = which(gsea_res@result$enrichmentScore < 0))
}
else{
message("All enrichment score are positive, showing those instead.")
graph <- enrichplot::gseaplot2(gsea_res,
geneSetID = which(gsea_res@result$enrichmentScore > 0))
}
}
graph[[1]]$labels$subtitle <- paste(database, " pvalueCutoff:", pval_cutoff)
graph[[1]] <- graph[[1]] +
theme(legend.position = "inside",
legend.position.inside = c(0.8,0.9),
legend.text = element_text(face = "bold"))
return(list("res" = res, "graph" = graph))
}
}
# function to always get most recent wiki pathway database (update every 10 of month)
get_wikipath <- function(wp = TRUE, species = "human"){
if(species == "human"){
species <- "Homo_sapiens"
}
else if(species == "mouse"){
species <- "Mus_musculus"
}
date <- strsplit(as.character(Sys.Date()), "-")[[1]]
date <- as.numeric(date)
if(date[3] < 11){
date[2] <- date[2] - 1
}
date[3] <- 10
if(date[2] == 0){
date[2] <- 12
date[1] <- date[1] - 1
}
else if(date[2] < 10){
date[2] <- paste0("0", date[2])
}
date <- paste0(date, collapse = "")
url_wiki <- paste0("https://wikipathways-data.wmcloud.org/", date, "/gmt/wikipathways-",
date, "-gmt-", species, ".gmt")
url_wiki <- url(url_wiki)
wikipath <- tryCatch({
if(wp){
clusterProfiler::read.gmt.wp(url_wiki)
}
else{
clusterProfiler::read.gmt(url_wiki)
}
},
# if wrong date
error = function(e){
date <- strsplit(date, "")[[1]][-(nchar(date)-1)]
date <- paste0(date, collapse = "")
date <- paste0(date, 1)
url_wiki <- paste0("https://wikipathways-data.wmcloud.org/", date, "/gmt/wikipathways-",
date, "-gmt-", species, ".gmt")
url_wiki <- url(url_wiki)
wikipath2 <- tryCatch({
if(wp){
clusterProfiler::read.gmt.wp(url_wiki)
}
else{
clusterProfiler::read.gmt(url_wiki)
}
},
# if wrong date again, retrieve one month
error = function(e){
date <- strsplit(date, "")[[1]]
date <- c(paste(date[1:4], collapse = ""), # year
paste(date[5:6], collapse = ""), # month
paste(date[7:8], collapse = "") # day
)
date[3] <- "10"
date[2] <- as.numeric(date[2]) - 1
date[2] <- ifelse(date[2] == "0", "12", date[2])
date[2] <- ifelse(nchar(date[2]) == 1, paste0("0", date[2]), date[2])
date[1] <- ifelse(date[2] == "12", as.numeric(date[1]) - 1, date[1])
date <- paste(date, collapse = "")
url_wiki <- paste0("https://wikipathways-data.wmcloud.org/", date, "/gmt/wikipathways-",
date, "-gmt-", species, ".gmt")
url_wiki <- url(url_wiki)
wikipath3 <- tryCatch({
if(wp){
clusterProfiler::read.gmt.wp(url_wiki)
}
else{
clusterProfiler::read.gmt(url_wiki)
}
},
# if wrong date
error = function(e) {
date <- strsplit(date, "")[[1]][-(nchar(date)-1)]
date <- paste0(date, collapse = "")
date <- paste0(date, 1)
url_wiki <- paste0("https://wikipathways-data.wmcloud.org/", date, "/gmt/wikipathways-",
date, "-gmt-", species, ".gmt")
url_wiki <- url(url_wiki)
if(wp){
wikipath4 <- clusterProfiler::read.gmt.wp(url_wiki)
}
else{
wikipath4 <-clusterProfiler::read.gmt(url_wiki)
}
return(wikipath4)
})
return(wikipath3)
})
return(wikipath2)
})
close(url_wiki)
return(wikipath)
}
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