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Prioritization & Data
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Included more tractability data in the output tables and updated the prioritization algorithm.
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@bpickett
bpickett authored Nov 10, 2022
1 parent 696200d commit a52e0f3
Showing 1 changed file with 41 additions and 8 deletions.
49 changes: 41 additions & 8 deletions Pathways2Targets2.R
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Original file line number Diff line number Diff line change
Expand Up @@ -46,12 +46,12 @@ sig_paths <- as.vector(in_data$Name)
sig_dbs <- as.vector(in_data$SourceDB)

for(i in 1:length(sig_dbs)){
#i <- 7
#i <- 1
print(paste0("Working...Pathway ",i," of ", length(sig_dbs)," : ",sig_paths[i]))

if(sig_dbs[i] == "KEGG"){
if(length(humanKEGG@entries[[sig_paths[i]]])==0){
print(paste0("Skipping...Pathway ",i,"of ", length(sig_dbs)," : ",sig_paths[i]," -- No Protein Data"))
print(paste0("Skipping...Pathway ",i," of ", length(sig_dbs)," : ",sig_paths[i]," -- No Protein Data"))
next()
}
db_entrezID <- as.vector(humanKEGG@entries[[sig_paths[i]]]@protEdges[["src"]])
Expand Down Expand Up @@ -158,6 +158,9 @@ for(i in 1:length(sig_dbs)){
safetyLiabilities {
event
}
subcellularLocations{
location
}
knownDrugs {
uniqueDrugs
rows {
Expand Down Expand Up @@ -208,20 +211,50 @@ for(i in 1:length(sig_dbs)){
#sum tractability at "approved", "advanced clinical trials", or "phase 1 trials" for SM, Ab, PR, and OC
for(z in 1:length(trac_vector)){
#z <- 1
if(length(target_data[["target"]][["tractability"]])>0){
if(length(target_data[["target"]][["tractability"]])==0){
sm_approved <- "Unknown"
sm_advancedClinical <- "Unknown"
sm_phase1 <- "Unknown"
ab_approved <- "Unknown"
ab_advancedClinical <- "Unknown"
ab_phase1 <- "Unknown"
pr_approved <- "Unknown"
pr_advancedClinical <- "Unknown"
pr_phase1 <- "Unknown"
oc_approved <- "Unknown"
oc_advancedClinical <- "Unknown"
oc_phase1 <- "Unknown"
}else if(length(target_data[["target"]][["tractability"]])>0){
sm_approved <- target_data[["target"]][["tractability"]][[1]][["value"]]
sm_advancedClinical <- target_data[["target"]][["tractability"]][[2]][["value"]]
sm_phase1 <- target_data[["target"]][["tractability"]][[3]][["value"]]
ab_approved <- target_data[["target"]][["tractability"]][[8]][["value"]]
ab_advancedClinical <- target_data[["target"]][["tractability"]][[9]][["value"]]
ab_phase1 <- target_data[["target"]][["tractability"]][[10]][["value"]]
pr_approved <- target_data[["target"]][["tractability"]][[18]][["value"]]
pr_advancedClinical <- target_data[["target"]][["tractability"]][[19]][["value"]]
pr_phase1 <- target_data[["target"]][["tractability"]][[20]][["value"]]
oc_approved <- target_data[["target"]][["tractability"]][[26]][["value"]]
oc_advancedClinical <- target_data[["target"]][["tractability"]][[27]][["value"]]
oc_phase1 <- target_data[["target"]][["tractability"]][[28]][["value"]]
if(target_data[["target"]][["tractability"]][[z]][["value"]]=="TRUE"){
tractability <- tractability+1
}
}
}
if(length(target_data[["target"]][["subcellularLocations"]])==0){
subCellLoc <- "No data"
}else if(length(target_data[["target"]][["subcellularLocations"]])>0){
subCellLoc <- as.vector(unlist(target_data[["target"]][["subcellularLocations"]][[1]]))
}
#make sure to only store unique records to
if(length(unique_chembl) == 0){
unique_chembl <- inter_col[1]
# #if drug has no approved indications, then add an N/A for the record
# if(length(inter_col == 5)){
# inter_col[6] <- as.character("N/A")
# }
temp_row <- c(target_data[["target"]][["id"]],target_data[["target"]][["approvedSymbol"]],target_data[["target"]][["approvedName"]],target_data[["target"]][["associatedDiseases"]][["count"]],tractability,length(target_data[["target"]][["safetyLiabilities"]]),target_data[["target"]][["knownDrugs"]][["uniqueDrugs"]],inter_col,sig_dbs[i], sig_paths[i])
temp_row <- as.vector(c(target_data[["target"]][["id"]],target_data[["target"]][["approvedSymbol"]],target_data[["target"]][["approvedName"]],target_data[["target"]][["associatedDiseases"]][["count"]],tractability,sm_approved,sm_advancedClinical,sm_phase1,ab_approved,ab_advancedClinical,ab_phase1,pr_approved,pr_advancedClinical,pr_phase1,oc_approved,oc_advancedClinical,oc_phase1,subCellLoc,length(target_data[["target"]][["safetyLiabilities"]]),target_data[["target"]][["knownDrugs"]][["uniqueDrugs"]],inter_col,sig_dbs[i], sig_paths[i]))
temp_row <- as.data.frame(t(temp_row))
merged_drugs <- as.data.frame(rbind(merged_drugs,temp_row),stringsAsFactors = FALSE, drop = FALSE)
#write.table(df_init, file = outfile, row.names = FALSE, col.names=TRUE, sep = "\t", append = FALSE)
Expand All @@ -235,7 +268,7 @@ for(i in 1:length(sig_dbs)){
if(length(inter_col == 5)){
inter_col[6] <- as.character("N/A")
}
temp_row <- c(target_data[["target"]][["id"]],target_data[["target"]][["approvedSymbol"]],target_data[["target"]][["approvedName"]],target_data[["target"]][["associatedDiseases"]][["count"]],tractability,length(target_data[["target"]][["safetyLiabilities"]]),target_data[["target"]][["knownDrugs"]][["uniqueDrugs"]],inter_col,sig_dbs[i], sig_paths[i])
temp_row <- as.vector(c(target_data[["target"]][["id"]],target_data[["target"]][["approvedSymbol"]],target_data[["target"]][["approvedName"]],target_data[["target"]][["associatedDiseases"]][["count"]],tractability,target_data[["target"]][["tractability"]][[1]][["value"]],target_data[["target"]][["tractability"]][[2]][["value"]],target_data[["target"]][["tractability"]][[3]][["value"]],target_data[["target"]][["tractability"]][[9]][["value"]],target_data[["target"]][["tractability"]][[10]][["value"]],target_data[["target"]][["tractability"]][[11]][["value"]],target_data[["target"]][["tractability"]][[18]][["value"]],target_data[["target"]][["tractability"]][[19]][["value"]],target_data[["target"]][["tractability"]][[20]][["value"]],target_data[["target"]][["tractability"]][[26]][["value"]],target_data[["target"]][["tractability"]][[27]][["value"]],target_data[["target"]][["tractability"]][[28]][["value"]],subCellLoc,length(target_data[["target"]][["safetyLiabilities"]]),target_data[["target"]][["knownDrugs"]][["uniqueDrugs"]],inter_col,sig_dbs[i], sig_paths[i]))
temp_row <- as.data.frame(t(temp_row))
merged_drugs <- as.data.frame(rbind(merged_drugs,temp_row),stringsAsFactors = FALSE)
}
Expand All @@ -253,7 +286,7 @@ for(i in 1:length(sig_dbs)){
rm(target_data)
}
}
colnames(merged_drugs) <- c("Target_ID","Target_Symbol","Target_Name","Associated_Disease_Count","Tractability_Count","Safety_Liabilities","Number_Unique_Drugs","Drug_ID","Drug_Name","Is_FDA_Approved","Highest_Clinical_Trial_Phase","Has_Been_Withdrawn","Pathway_DB","Pathway_Name")
colnames(merged_drugs) <- c("Target_ID","Target_Symbol","Target_Name","Associated_Disease_Count","Tractability_Count","sm_approved","sm_advancedClinical","sm_phase1","ab_approved","ab_advancedClinical","ab_phase1","pr_approved","pr_advancedClinical","pr_phase1","oc_approved","oc_advancedClinical","oc_phase1","Subcellular_Location","Safety_Liabilities","Number_Unique_Drugs","Drug_ID","Drug_Name","Is_FDA_Approved","Highest_Clinical_Trial_Phase","Has_Been_Withdrawn","Pathway_DB","Pathway_Name")
##colnames(merged_drugs) <- c("Target_ID","Target_Symbol","Target_Name","Drug_ID","Drug_Name","Is_FDA_Approved","Highest_Clinical_Trial_Phase","Has_Been_Withdrawn","Pathway_DB","Pathway_Name")
#merged_drugs <- unique(merged_drugs)
#write.table(merged_drugs, file = outfile, row.names = FALSE, col.names=TRUE, sep = "\t", append = FALSE)
Expand Down Expand Up @@ -342,7 +375,7 @@ rm(phase_temp)
num_df <- as.data.frame(cbind(target1,numApprovedv, num3v, num2v, num1v, num4v))
merged_drugs <- merge(merged_drugs,num_df, by.x='Target_Symbol', by.y='target1')

colnames(merged_drugs) <- c("Target_Symbol","Target_ID","Target_Name","Associated_Disease_Count","Tractability_Count","Safety_Liabilities","Number_Unique_Drugs","Drug_ID","Drug_Name","Is_FDA_Approved","Highest_Clinical_Trial_Phase","Has_Been_Withdrawn","Pathway_DB","Pathway_Name","Target_in_Pathways","num_Approved_Drugs","num_Phase3","num_Phase2","num_Phase1","num_Phase4")
colnames(merged_drugs) <- c("Target_Symbol","Target_ID","Target_Name","Associated_Disease_Count","Tractability_Count","sm_approved","sm_advancedClinical","sm_phase1","ab_approved","ab_advancedClinical","ab_phase1","pr_approved","pr_advancedClinical","pr_phase1","oc_approved","oc_advancedClinical","oc_phase1","Subcellular_Location","Safety_Liabilities","Number_Unique_Drugs","Drug_ID","Drug_Name","Is_FDA_Approved","Highest_Clinical_Trial_Phase","Has_Been_Withdrawn","Pathway_DB","Pathway_Name","Target_in_Pathways","num_Approved_Drugs","num_Phase3","num_Phase2","num_Phase1","num_Phase4")
merged_drugs$Tractability_Count <- as.numeric(as.character(merged_drugs$Tractability_Count))
merged_drugs$Safety_Liabilities <- as.numeric(as.character(merged_drugs$Safety_Liabilities))
merged_drugs$Number_Unique_Drugs <- as.numeric(as.character(merged_drugs$Number_Unique_Drugs))
Expand Down Expand Up @@ -371,7 +404,7 @@ for(j in 1:nrow(merged_drugs)){
weighted_score_col[j] <- weighted_score
}
merged_drugs$Weighted_Score <- weighted_score_col
colnames(merged_drugs) <- c("Target_Symbol","Target_ID","Target_Name","Associated_Disease_Count","Tractability_Count","Safety_Liabilities","Number_Unique_Drugs","Drug_ID","Drug_Name","Is_FDA_Approved","Highest_Clinical_Trial_Phase","Has_Been_Withdrawn","Pathway_DB","Pathway_Name","Target_in_Pathways","num_Approved_Drugs","num_Phase3","num_Phase2","num_Phase1","num_Phase4","Weighted_Score")
colnames(merged_drugs) <- c("Target_Symbol","Target_ID","Target_Name","Associated_Disease_Count","Tractability_Count","sm_approved","sm_advancedClinical","sm_phase1","ab_approved","ab_advancedClinical","ab_phase1","pr_approved","pr_advancedClinical","pr_phase1","oc_approved","oc_advancedClinical","oc_phase1","Subcellular_Location","Safety_Liabilities","Number_Unique_Drugs","Drug_ID","Drug_Name","Is_FDA_Approved","Highest_Clinical_Trial_Phase","Has_Been_Withdrawn","Pathway_DB","Pathway_Name","Target_in_Pathways","num_Approved_Drugs","num_Phase3","num_Phase2","num_Phase1","num_Phase4","Weighted_Score")

merged_drugs <- merged_drugs[order(-merged_drugs$Weighted_Score,
-merged_drugs$Target_in_Pathways,
Expand Down

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