#' @title GOenrichment
#'
#' @description Perform GO enrichment analysis with topGO package.
#' This package provides tools for testing GO terms while accounting for
#' the topology of the GO graph. Different test statistics and different
#' methods for eliminating local similarities and dependencies between GO
#' terms can be implemented and applied.
#'
#' @param resDEG data frame contains for each contrast the significance expression (1/0/-1) for all gene.
#' @param data_list list contain all data and metadata (DGEList, samples descriptions, contrast, design and annotations).
#' @param parameters list that contains all arguments charged in Asko_start.
#' @param list gene list of interest if you want to apply GOenrichment function on a specific gene list.
#' @param title name of the gene list if you want to apply GOenrichment function on a specific gene list.
#' @return none.
#'
#' @import topGO
#' @import goSTAG
#' @import ggplot2
#'
#' @examples
#' \dontrun{
#' GOenrichment(resDEG, data_list, parameters)
#' # OR
#' GOenrichment(resDEG, data_list, parameters, list, title)
#' # OR
#' GOenrichment(resDEG, data_list, parameters, list=NULL, title=NULL)
#' }
#'
#' @note Remember to read the Wiki section in \url{https://github.com/askomics/askoR/wiki}
#' @export
GOenrichment<-function(resDEG, data_list, parameters, list=NULL, title=NULL){
study_dir = paste0(parameters$dir_path,"/", parameters$analysis_name, "/")
input_path = paste0(parameters$dir_path, "/input/")
norm_dir = paste0(study_dir, "NormCountsTables/")
GO_dir = paste0(study_dir, "/GOenrichment/")
if(dir.exists(GO_dir)==FALSE){
dir.create(GO_dir)
cat("\n\nDirectory: ",GO_dir," created\n")
}
# Get GO annotations
geneID2GO <- topGO::readMappings(file = paste0(input_path,parameters$geneID2GO_file))
geneNames <- names(geneID2GO)
if (is.null(list) == FALSE){
img_go_dir = paste0(GO_dir,title,"/")
if(dir.exists(img_go_dir)==FALSE){
dir.create(img_go_dir)
cat("Directory: ",img_go_dir," created\n")
}
GeneListName = title
geneSelected = list
}
else if (parameters$GO == "up") {
img_go_dir = paste0(GO_dir,"UP_DEgenes/")
if(dir.exists(img_go_dir)==FALSE){
dir.create(img_go_dir)
cat("\n\nDirectory: ",img_go_dir," created\n")
}
GeneListName = colnames(data_list$contrast)
}
else if (parameters$GO == "down") {
img_go_dir = paste0(GO_dir,"DOWN_DEgenes/")
if(dir.exists(img_go_dir)==FALSE){
dir.create(img_go_dir)
cat("\n\nDirectory: ",img_go_dir," created\n")
}
GeneListName = colnames(data_list$contrast)
}
else {
img_go_dir = paste0(GO_dir,"TOTAL_DEgenes/")
if(dir.exists(img_go_dir)==FALSE){
dir.create(img_go_dir)
cat("\n\nDirectory: ",img_go_dir," created\n")
}
GeneListName = colnames(data_list$contrast)
}
for(contrast in GeneListName){
# transfo resDEG vector to dataframe si on a un seul contraste
if (ncol(resDEG)==1) {
row = rownames(resDEG)
resDEG = data.frame(x=row, contrast=resDEG[,1])
colnames(resDEG) = c("NA",contrast)
rownames(resDEG) = row
}
if (is.null(list) == TRUE){
if(is.null(parameters$GO)==TRUE){ return(NULL) }
if(parameters$GO == "both"){
geneSelected <- rownames(resDEG[apply(as.matrix(resDEG[,contrast]), 1, function(x) all(x!=0)),])
titlename<-"all differentially expressed genes (up+down)"
}else if(parameters$GO == "up"){
geneSelected<-rownames(resDEG[apply(as.matrix(resDEG[,contrast]), 1, function(x) all(x==1)),])
titlename<-"genes expressed UP"
}else if(parameters$GO == "down"){
geneSelected<-rownames(resDEG[apply(as.matrix(resDEG[,contrast]), 1, function(x) all(x==-1)),])
titlename<-"genes expressed DOWN"
}else{
cat("\nBad value for GO parameters : autorized values are both, up, down or NULL.\n")
return(NULL)
}
}
geneList <- factor(as.integer(geneNames %in% geneSelected))
names(geneList) <- geneNames
img_GOtoGene_dir = paste0(img_go_dir, contrast,"_SignificantGO/")
if(dir.exists(img_GOtoGene_dir)==FALSE){
dir.create(img_GOtoGene_dir)
cat("Directory: ",img_GOtoGene_dir," created\n")
}
if(length(geneSelected)==0){
cat("\nContrast:",contrast,"-> No DE genes found!\n")
next
}
if(sum(levels(geneList)==1)==0){
cat("\nContrast:",contrast,"-> No DE genes with GO annotation!\n")
next
}
listOnto <- c("MF","BP","CC")
for(ontology in listOnto){
cat("\nContrast :",contrast," et ontologie :",ontology,"\n")
GOdata <- methods::new("topGOdata",
nodeSize = parameters$GO_min_num_genes,
ontology = ontology,
allGenes = geneList,
annot = annFUN.gene2GO,
gene2GO = geneID2GO)
resultTest <- topGO::runTest(GOdata, algorithm = parameters$GO_algo, statistic = parameters$GO_stats)
resGenTab <- topGO::GenTable(GOdata, numChar = 1000000, statisticTest = resultTest, orderBy = "statisticTest", topNodes=length(graph::nodes(graph(GOdata))) )
resGenTab$Ratio = as.numeric(as.numeric(resGenTab$Significant)/as.numeric(resGenTab$Expected))
resGenTab$GO_cat <- ontology
if (is.null(parameters$annotation)==FALSE){
annot<-utils::read.csv(paste0(input_path, parameters$annotation), header = TRUE, row.names = 1, sep = '\t', quote = "")
}
# import normalized MEAN counts in CPM
moys<-utils::read.csv(paste0(norm_dir, parameters$analysis_name,"_CPM_NormMeanCounts.txt"), header=TRUE, sep="\t", row.names=1)
moys = as.matrix(moys)
# Create files of genes for each enrichied GO
myterms = as.character(resGenTab$GO.ID[as.numeric(resGenTab$statisticTest)<=parameters$GO_threshold])
if (length(myterms) != "0"){
cat("\nAskoR is saving one file per enriched GO-term (category ", ontology, ").\n")
mygenes <- genesInTerm(GOdata, myterms)
noms=names(mygenes)
nomss=stringr::str_replace(noms,":","_")
for (z in seq_len(length(mygenes))){
listes=mygenes[[z]][mygenes[[z]] %in% geneSelected == TRUE]
GOtab <- data.frame(Gene=listes)
#GOtab$Gene_cluster = clustered
rownames(GOtab)=GOtab$Gene
if (is.null(parameters$annotation)==FALSE){
GOtab = merge(GOtab, annot, by="row.names")
GOtab = GOtab[,-1]
GOtab = GOtab[,seq_len(2)]
colnames(GOtab)[2] <- "Gene_description"
rownames(GOtab)=GOtab$Gene
}
else{
GOtab$Gene_description = "No annotation file provided"
}
GOtab = merge(GOtab, resDEG, by="row.names")
GOtab = GOtab[,-1]
rownames(GOtab)=GOtab$Gene
GOtab = merge(GOtab, moys, by="row.names")
GOtab = GOtab[,-1]
GOtab$GO_ID = noms[z]
GOtab$GO_term = resGenTab[which(resGenTab$GO.ID==noms[z]),2]
GOtab$GO_cat = resGenTab[which(resGenTab$GO.ID==noms[z]),8]
utils::write.table(GOtab,paste0(img_GOtoGene_dir, ontology, "_", nomss[z],".txt"), sep="\t", dec=".", row.names=FALSE, col.names=TRUE, quote=FALSE)
}
}
if(ontology == "MF"){
TabCompl<-resGenTab
resGenTab[resGenTab=="< 1e-30"]<-"1.0e-30"
if(nrow(resGenTab[as.numeric(resGenTab$statisticTest) <= parameters$GO_threshold & resGenTab$Ratio >= parameters$Ratio_threshold & resGenTab$Significant >= parameters$GO_min_sig_genes,])!=0){
maxi<-parameters$GO_max_top_terms
TabSigCompl<-resGenTab[as.numeric(resGenTab$statisticTest) <= parameters$GO_threshold & resGenTab$Ratio >= parameters$Ratio_threshold & resGenTab$Significant >= parameters$GO_min_sig_genes,]
if(maxi > nrow(TabSigCompl)){ maxi<-nrow(TabSigCompl) }
TabSigCompl<-TabSigCompl[seq_len(maxi),]
}else{
cat("\n\n->",contrast," - ontology: ",ontology," - No enrichment can pe performed - there are no feasible GO terms!\n\n")
TabSigCompl<-as.data.frame(stats::setNames(replicate(8,numeric(0), simplify=FALSE),c("GO.ID","Term","Annotated","Significant","Expected","statisticTest","Ratio","GO_cat") ))
}
}else{
TabCompl=rbind(TabCompl,resGenTab)
resGenTab[resGenTab=="< 1e-30"]<-"1.0e-30"
if(nrow(resGenTab[as.numeric(resGenTab$statisticTest) <= parameters$GO_threshold & resGenTab$Ratio >= parameters$Ratio_threshold & resGenTab$Significant >= parameters$GO_min_sig_genes,])!=0){
maxi<-parameters$GO_max_top_terms
tempSig<-resGenTab[as.numeric(resGenTab$statisticTest) <= parameters$GO_threshold & resGenTab$Ratio >= parameters$Ratio_threshold & resGenTab$Significant >= parameters$GO_min_sig_genes,]
if(maxi > nrow(tempSig)){ maxi<-nrow(tempSig) }
TabSigCompl=rbind(TabSigCompl,tempSig[seq_len(maxi),])
}else{
cat("\n\n->",contrast," - ontology: ",ontology," - No enrichment can pe performed - there are no feasible GO terms!\n\n")
}
}
## Bargraph in each GO cat separately (ratio, pval, and number of genes)
GoCoul="gray"
if (is.null(list) == FALSE){
GraphTitle0 = paste0("GO Enrichment (",ontology, " category)", "\n for list ", contrast, "\n (",length(which(geneList==1)), " annotated genes among ",length(geneSelected)," genes)")
}
else{
GraphTitle0 = paste0("GO Enrichment (",ontology, " category)", "\n for contrast ", contrast, "\n (",length(which(geneList==1)), " annotated genes among ",length(geneSelected)," genes)")
}
if(exists("TabSigCompl")==TRUE){
if(nrow(TabSigCompl[TabSigCompl$GO_cat==ontology,])>=1){
TabOntology<-TabSigCompl[TabSigCompl$GO_cat==ontology,]
ggplot2::ggplot(TabOntology, aes(x=stringr::str_wrap(TabOntology$Term, 55), y=TabOntology$Ratio,fill=-1*log10(as.numeric(TabOntology$statisticTest)))) +
coord_flip()+
geom_col()+
theme_classic()+
geom_text(aes(label=TabOntology$Significant), position=position_stack(0.5),color="white")+
scale_fill_gradient(name="-log10pval",low=GoCoul,high=paste0(GoCoul,"4"))+
scale_y_reverse()+
labs(title = GraphTitle0, x="GOterm", y="Ratio Significant / Expected") +
scale_x_discrete(position = "top")+
theme(
axis.text.y = element_text(face="bold",size=10),
axis.text.x = element_text(face="bold",size=10),
axis.title.x=element_text(face="bold",size=12),
axis.title.y=element_blank(),
legend.title = element_text(size=12,face="bold"),
plot.title = element_text(face="bold",size=15),
legend.text = element_text(size=12),
panel.background = element_rect(colour = "black", size=0.5, fill=NA))
ggplot2::ggsave(filename=paste0(img_go_dir,contrast,"_",ontology,"_GOgraph.png"),width=10, height = 8)
}
}
}
TabCompl<-TabCompl[TabCompl$Significant > 0,]
utils::write.table(TabCompl, file=paste0(img_go_dir, parameters$analysis_name, "_", contrast, "_Complet_GOenrichment.txt"), col.names=TRUE, row.names=FALSE, quote=FALSE, sep='\t')
if(exists("TabSigCompl")==TRUE){
if(nrow(TabSigCompl)>=1){
if (parameters$GO_max_top_terms > 10) {
TabSigCompl$Term = stringr::str_trunc(TabSigCompl$Term, 67)
}else{
TabSigCompl$Term = stringr::str_trunc(TabSigCompl$Term, 137)
}
# Graph for one contrast
comp_names <- c( `MF` = "Molecular Function", `BP` = "Biological Process", `CC` = "Cellular Component")
coul <- c(`MF` = "green4", `BP` = "red", `CC` = "blue")
comp_names2 <- c(`MF` = "MF", `BP` = "BP", `CC` = "CC")
TabSigCompl$Term = factor(TabSigCompl$Term, levels = unique(TabSigCompl$Term))
minR=(min(TabSigCompl$Ratio)+max(TabSigCompl$Ratio))/4
minP=(min(as.numeric(TabSigCompl$statisticTest))+max(as.numeric(TabSigCompl$statisticTest)))/4
if (parameters$GO == "both"){
GraphTitleList = paste0("GO Enrichment for list\n",contrast, "\n (Total DE)", "\n (",length(which(geneList==1)), " annotated genes among ",length(geneSelected)," genes)")
GraphTitleContrast = paste0("GO Enrichment for contrast\n",contrast, "\n (Total DE)", "\n (",length(which(geneList==1)), " annotated genes among ",length(geneSelected)," genes)")
}
if (parameters$GO == "up"){
GraphTitleList = paste0("GO Enrichment for list\n",contrast, "\n (UP DE)", "\n (",length(which(geneList==1)), " annotated genes among ",length(geneSelected)," genes)")
GraphTitleContrast = paste0("GO Enrichment for contrast\n",contrast, "\n (UP DE)", "\n (",length(which(geneList==1)), " annotated genes among ",length(geneSelected)," genes)")
}
if (parameters$GO == "down"){
GraphTitleList = paste0("GO Enrichment for list\n",contrast, "\n (DOWN DE)", "\n (",length(which(geneList==1)), " annotated genes among ",length(geneSelected)," genes)")
GraphTitleContrast = paste0("GO Enrichment for contrast\n",contrast, "\n (DOWN DE)", "\n (",length(which(geneList==1)), " annotated genes among ",length(geneSelected)," genes)")
}
if (is.null(list) == FALSE){
GraphTitle = GraphTitleList
}
else{
GraphTitle = GraphTitleContrast
}
# Ratio Graph
ggplot2::ggplot(TabSigCompl, aes(x=TabSigCompl$Ratio, y=TabSigCompl$Term, size=TabSigCompl$Significant, color=TabSigCompl$GO_cat)) +
geom_point(alpha=1) +
labs(title = GraphTitle, x="Ratio Significant/Expected", y="GOterm")+
scale_color_manual(values=coul,labels=comp_names,name="GO categories") +
facet_grid(TabSigCompl$GO_cat~., scales="free", space = "free",labeller = as_labeller(comp_names2)) +
scale_size_continuous(name="Number of genes") + scale_x_continuous(expand = expansion(add = minR)) +
scale_y_discrete(labels = function(x) stringr::str_wrap(x, width = 70)) + theme_linedraw() +
theme(
panel.background = element_rect(fill = "grey90", colour = "grey90", size = 0.5, linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid', colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid', colour = "white"),
axis.text.y = element_text(face="bold", size=rel(0.75)),
axis.text.x = element_text(face="bold", size=rel(0.75)),
axis.title = element_text(face="bold", size=rel(0.75)),
legend.title = element_text(size=rel(0.75), face="bold"),
plot.title = element_text(face="bold", size=rel(1), hjust=1),
legend.text = element_text(size=rel(0.5)))
ggplot2::ggsave(filename=paste0(img_go_dir,contrast,"_Ratio_BUBBLESgraph.png"), width=7, height=7)
# Pvalue Graph
ggplot2::ggplot(TabSigCompl, aes(x=as.numeric(TabSigCompl$statisticTest), y=TabSigCompl$Term, size=TabSigCompl$Significant, color=TabSigCompl$GO_cat)) +
geom_point(alpha=1) + labs(title = GraphTitle,x="Pvalue",y="GOterm")+
scale_color_manual(values=coul,labels=comp_names,name="GO categories")+
facet_grid(TabSigCompl$GO_cat~., scales="free", space = "free",labeller = as_labeller(comp_names2))+
scale_size_continuous(name="Number of genes") + scale_x_continuous(expand = expansion(add = minP)) +
scale_y_discrete(labels = function(x) stringr::str_wrap(x, width = 70)) + theme_linedraw() +
scale_x_reverse()+
theme(
panel.background = element_rect(fill = "grey90", colour = "grey90", size = 0.5, linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid', colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid', colour = "white"),
axis.text.y = element_text(face="bold", size=rel(0.75)),
axis.text.x = element_text(face="bold", size=rel(0.75), angle=45, hjust=1),
axis.title = element_text(face="bold", size=rel(0.75)),
legend.title = element_text(size=rel(0.75), face="bold"),
plot.title = element_text(face="bold", size=rel(1), hjust=1),
legend.text = element_text(size=rel(0.5)))
ggplot2::ggsave(filename=paste0(img_go_dir,contrast,"_Pvalue_BUBBLESgraph.png"), width=7, height=7)
}
}else{
cat("\n\nToo few results to display the graph.\n\n")
}
}
}
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