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sCRAP.R
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sCRAP.R
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#############################################################
# selective Cross Reactive Antigen Presentation (sCRAP)
# (Feb 2023 edit - Original code published in 2021)
# Alvin Farrel, Mark Yarmarkovic
# Maris Lab
# Children's Hospital of Philadelphia
# Feb 19 2023
#############################################################
suppressPackageStartupMessages(library(optparse))
option_list <- list(
make_option(c("-p", "--peptide"),default = "", type = "character",
help = "(Required) Peptide query - typically about 9 peptides {character string}"),
make_option(c("-l", "--hla"),default = "", type = "character",
help = "(Required) hla allele in format: HLA-{allele}, eg.'HLA-A0201' 'HLA-A0301' "),
make_option(c("-s", "--hotspots"), type = "character",default = "4,5,6",
help = "hotspots locations, numeric value 1-9 seperated by commas - {default: 4,5,6}"),
make_option(c("-o", "--outdir"), type = "character",
help = "Output directory path", default = "."),
make_option(c("-f", "--filename"), default = "", type = "character",
help = "Output file basename"),
make_option(c("-d", "--datadir"), default = "data/", type = "character",
help = "data directory path"),
make_option(c("-m", "--hladir"), default = "HLA/", type = "character",
help = "hla data directory path"),
make_option(c("-t", "--filetype"), default = "csv", type = "character",
help = "select output file format (csv/tsv) {default: csv}")
)
CHECKS = TRUE
# parse the parameters
CHECKS=tryCatch(expr={
parse_args(OptionParser(option_list = option_list,add_help_option = T),print_help_and_exit = T);
TRUE
}, error=function(e){
cat("\nThere was an error with your input arguments")
return(F)
}
)# tryCatch({
if(CHECKS)
{
opt <- parse_args(OptionParser(option_list = option_list,add_help_option = T),print_help_and_exit = T)
hla_options = c("HLA-A0101","HLA-A0201","HLA-A0202","HLA-A0203","HLA-A0205","HLA-A0206","HLA-A0207","HLA-A0211","HLA-A0212","HLA-A0216","HLA-A0217","HLA-A0219","HLA-A0250","HLA-A0301","HLA-A0302","HLA-A0319","HLA-A1101","HLA-A2301","HLA-A2402","HLA-A2403","HLA-A2501","HLA-A2601","HLA-A2602","HLA-A2603","HLA-A2902","HLA-A3001","HLA-A3002","HLA-A3101","HLA-A3201","HLA-A3207","HLA-A3215","HLA-A3301","HLA-A6601","HLA-A6801","HLA-A6802","HLA-A6823","HLA-A6901","HLA-A8001","HLA-B0702","HLA-B0801","HLA-B0802","HLA-B0803","HLA-B1401","HLA-B1402","HLA-B1501","HLA-B1502","HLA-B1503","HLA-B1509","HLA-B1517","HLA-B1801","HLA-B2705","HLA-B2720","HLA-B3501","HLA-B3503","HLA-B3701","HLA-B3801","HLA-B3901","HLA-B4001","HLA-B4002","HLA-B4013","HLA-B4201","HLA-B4402","HLA-B4403","HLA-B4501","HLA-B4506","HLA-B4601","HLA-B4801","HLA-B5101","HLA-B5301","HLA-B5401","HLA-B5701","HLA-B5703","HLA-B5801","HLA-B5802","HLA-B7301","HLA-B8101","HLA-B8301","HLA-C0303","HLA-C0401","HLA-C0501","HLA-C0602","HLA-C0701","HLA-C0702","HLA-C0802","HLA-C1203","HLA-C1402","HLA-C1502")
input_PepIn <- opt$peptide
input_HLA <- opt$hla
input_hotspots <- unlist(strsplit(opt$hotspots,split=","))
input_outdir <- opt$outdir
input_filename <- opt$filename
input_datadir <- opt$datadir
input_hladir <- opt$hladir
input_filetype <- tolower(opt$filetype)
if(nchar(input_PepIn) <= 3)
{
cat("\nError: Enter a peptide sequence\n")
CHECKS = F
}
if(length(which(input_HLA %in% hla_options)) < 1)
{
cat("\nError: Enter a valid HLA sequence with the '-l' option (See below).\nValid options inlcude:\n")
cat(paste(" ",paste(hla_options[1:10],collapse = " "),"\n"))
cat(paste(" ",paste(hla_options[11:20],collapse = " "),"\n"))
cat(paste(" ",paste(hla_options[21:30],collapse = " "),"\n"))
cat(paste(" ",paste(hla_options[31:40],collapse = " "),"\n"))
cat(paste(" ",paste(hla_options[41:50],collapse = " "),"\n"))
cat(paste(" ",paste(hla_options[51:60],collapse = " "),"\n"))
cat(paste(" ",paste(hla_options[61:70],collapse = " "),"\n"))
cat(paste(" ",paste(hla_options[71:80],collapse = " "),"\n"))
cat(paste(" ",paste(hla_options[80:87],collapse = " "),"\n"))
CHECKS = F
}
if(input_hotspots[1] == "0")
{
input_hotspots = c()
}
if(length(input_hotspots) >= 1)
{
input_hotspots = as.numeric(input_hotspots)[which(as.numeric(input_hotspots) > 0 & as.numeric(input_hotspots) <= 9) ]
}
if(length(input_hotspots) >= 1)
{
input_hotspots = as.numeric(input_hotspots)[which(as.numeric(input_hotspots) > 0 & as.numeric(input_hotspots) <= 9) ]
}
if(input_filetype != "csv" & input_filetype != "tsv")
{
input_filetype = "csv"
}
DATA_File_Check = c("allelelist.RDS","gtex_annot.RDS","genekey.RDS","gtex_p0.RDS","gtex_p1.RDS","gtex_p2.RDS","gtex_p3.RDS","gtex_p4.RDS","gtex_p5.RDS","gtex_p6.RDS","gtex_p7.RDS","gtex_p8.RDS","gtex_p9.RDS","combined_normal_ligands.RDS")
HLAfiles <- list.files(path=input_hladir, pattern = "*.RDS")
Datafiles <- list.files(path=input_datadir, pattern = "*.RDS")
if(!all(DATA_File_Check %in% Datafiles))
{
CHECKS = F
cat("\nError: Please enter a valid data directory and ensure all the required files are present:\n")
cat(paste(" ",paste(DATA_File_Check[1:3],collapse = " "),"\n"))
cat(paste(" ",paste(DATA_File_Check[4:6],collapse = " "),"\n"))
cat(paste(" ",paste(DATA_File_Check[7:9],collapse = " "),"\n"))
cat(paste(" ",paste(DATA_File_Check[10:12],collapse = " "),"\n"))
cat(paste(" ",paste(DATA_File_Check[13:14],collapse = " "),"\n"))
}
if(nchar(input_filename) == 0 )
{
out_file = paste("Result_",input_PepIn,"_",input_HLA,".",input_filetype,sep="")
}
if(nchar(input_filename) >= 1 )
{
out_file = paste(input_filename,".",input_filetype,sep="")
}
Output_Path = paste(input_outdir,"/",out_file,sep="")
} #if(CHECKS)
if(!CHECKS)
{
cat(paste("\nUsage: Rscript sCRAP.R -p <peptide> -l <HLA-allele> {arguments}\n\nuse:\n\n Rscript sCRAP.R -h \n\nfor more help.\n\n"))
} #if(!CHECKS)
if(CHECKS){
HLAfiles <- list.files(path=input_hladir, pattern = "*.RDS")
cat(" Loading Data...\n")
gtex_annot <- readRDS(paste(input_datadir,"/gtex_annot.RDS",sep=""))
genekey <- readRDS(paste(input_datadir,"/genekey.RDS",sep=""))
gtex_p0 <- readRDS(paste(input_datadir,"/gtex_p0.RDS",sep=""))
gtex_p1 <- readRDS(paste(input_datadir,"/gtex_p1.RDS",sep=""))
gtex_p2 <- readRDS(paste(input_datadir,"/gtex_p2.RDS",sep=""))
gtex_p3 <- readRDS(paste(input_datadir,"/gtex_p3.RDS",sep=""))
gtex_p4 <- readRDS(paste(input_datadir,"/gtex_p4.RDS",sep=""))
gtex_p5 <- readRDS(paste(input_datadir,"/gtex_p5.RDS",sep=""))
gtex_p6 <- readRDS(paste(input_datadir,"/gtex_p6.RDS",sep=""))
gtex_p7 <- readRDS(paste(input_datadir,"/gtex_p7.RDS",sep=""))
gtex_p8 <- readRDS(paste(input_datadir,"/gtex_p8.RDS",sep=""))
gtex_p9 <- readRDS(paste(input_datadir,"/gtex_p9.RDS",sep=""))
gtex <- rbind(gtex_p0,gtex_p1,gtex_p2,gtex_p3,gtex_p4,gtex_p5,gtex_p6,gtex_p7,gtex_p8,gtex_p9)
combined <- readRDS(paste(input_datadir,"/combined_normal_ligands.RDS",sep=""))
G=list()
G[[1]] = c("A","G") #Short Chains
G[[2]] = c("K","R","H") #Basic
G[[3]] = c("N","Q") #Polar Uncharged
G[[4]] = c("D","E") #Acidic
G[[5]] = c("C", "M") #Contains S
G[[6]] = c("F","Y","W","H") #Aromatic
G[[7]] = c("S","T","Y") #Alcohol-Hydroxyl Group
G[[8]] = c("I","L","V","M","A") #Aliphatic
G[[9]] = c("P") #Weird - I mean proline
Polarity = list()
Polarity[[1]] = c("D","E","N","Q","R","K","H","Y","C","S","T") #Polar
Polarity[[2]] = c("G","A","F","W","P","I","L","V","M") #Non Polar
Charge = list()
Charge[[1]] = c("D","E") #Negative
Charge[[2]] = c("K","R","H") #Positive
HLA_RDS_Files <- system(paste("ls HLA/", input_HLA, ".p*.RDS", sep=""), intern=T)
combinedpeps <- data.frame()
for(I in 1:length(HLA_RDS_Files))
{
combinedpeps <- rbind(combinedpeps,data.frame(readRDS(HLA_RDS_Files[I])))
}
peptable <- combinedpeps[,c(3,11,13,15)]
peptable$Identity <- as.character(gsub("_HUMAN","", as.character(peptable$Identity)))
#Function to Compare Peptides
Get_Peptide_Scores = function(QUERY,PEPTIDE)
{
QUERY.array = unlist(strsplit(as.character(QUERY),split=""))
PEPTIDE.array = unlist(strsplit(as.character(PEPTIDE),split=""))
Peptide_Score = -100
if(
length(QUERY.array) == length(PEPTIDE.array) #&
)#if
{#Start function
TEST.Pair=rbind(QUERY.array,PEPTIDE.array)
#Equivalent
EQU_score = apply(TEST.Pair,MARGIN = 2,function(x) {Score=0;Criteria = x[1]==x[2]; if(Criteria){Score=3};return(Score)})
#GROUP
GROUP_score = apply(TEST.Pair,MARGIN=2,function(X) {Score=0;Criteria=any(unlist(lapply(G,function(G) all(X %in% G))));if(Criteria){Score=2};return(Score)} )
#Polarity
Polarity_score = apply(TEST.Pair,MARGIN=2,function(X) {Score=0;Criteria=any(unlist(lapply(Polarity,function(G) all(X %in% G))));if(!Criteria){Score=-2};return(Score)})
#Charge
Charge_score = apply(TEST.Pair,MARGIN=2,function(X) {Score=0;Criteria=all(unlist(lapply(Charge, function(x) any(x %in% G))));if(!Criteria){Score=-1};return(Score)})
#Double Scores for Selected Hotspots.
HOTSPOTS <- as.numeric(unlist(input_hotspots))
EQU_score[HOTSPOTS] = EQU_score[HOTSPOTS]*2
GROUP_score[HOTSPOTS] = GROUP_score[HOTSPOTS]*2
Polarity_score[HOTSPOTS] = Polarity_score[HOTSPOTS]*2
Charge_score[HOTSPOTS] = Charge_score[HOTSPOTS]*2
#Sets scores at Positions 2 and last position to 0.
EQU_score[c(2,length(EQU_score))] = 0
GROUP_score[c(2,length(GROUP_score))] = 0
Charge_score[c(2,length(Charge_score))] = 0
#Final Match Score
Peptide_Score = sum(c(EQU_score,GROUP_score,Polarity_score))
}#{Start function
return(Peptide_Score)
}
#normal tissue RPKM
normal <- function(peptide){
for (i in 1:nrow(peptide)){
if (!is.na(g <- match(peptide$Gene[i], genekey$name))){
g <- match(peptide$Gene[i], genekey$name)
peptide$Gene[i] <- genekey$gene[g]
}
if (!is.na(match(peptide$Gene[i], rownames(gtex)))){
r <- match(peptide$Gene[i], rownames(gtex))
peptide$max_norm[i] <- max(gtex[r,])
tiss <- match(colnames(gtex)[which.max(gtex[r,])[[1]]], gtex_annot$SAMPID)
peptide$max_tissue[i] <- as.character(gtex_annot$SMTS[as.numeric(tiss)])
}
else {
peptide$max_norm[i] <- NA
peptide$max_tissue[i] <- NA
}
} #for (i in 1:nrow(peptide)) (end)
return(peptide)
} #normal <- function(peptide) (end)
# compare to normal ligandome
ligandome <- function(peptide){
peptide$Normal_Ligandome <- "F"
peptide$MHC_class <- ""
peptide$HLA <- ""
peptide$Organism <- ""
for (i in 1:nrow(peptide)){
if (!is.na(match(peptide$Peptide[i], combined$search_hit))){
r <- match(peptide$Peptide[i], combined$search_hit)
peptide$Normal_Ligandome[i] <- "T"
peptide$MHC_class[i] <- as.character(combined$MHCClass[r])
peptide$HLA[i] <- as.character(combined$top_allele[r])
peptide$Organism[i] <- as.character(combined$Organism[r])
}
else{
peptide$Normal_Ligandome[i] <- "F"
}
} #for (i in 1:nrow(peptide)) (end)
return(peptide)
} #ligandome <- function(peptide) (end)
{
PEPTIDE_INPUT = input_PepIn
cat(" Filtering table: this can take several minutes\n")
peptable.peptide.subset = peptable$peptide[which(sapply(as.character(peptable$peptide),nchar) == nchar(PEPTIDE_INPUT) & peptable$BindLevel=="<=SB")]
peptable.peptide.subset = peptable.peptide.subset[which((substr(peptable.peptide.subset, 1,1) == substr(PEPTIDE_INPUT, 1,1)) | (substr(peptable.peptide.subset, 3,3) == substr(PEPTIDE_INPUT, 3,3)) | (substr(peptable.peptide.subset, 4,4) == substr(PEPTIDE_INPUT, 4,4)) | (substr(peptable.peptide.subset, 5,5) == substr(PEPTIDE_INPUT, 5,5)) | (substr(peptable.peptide.subset, 6,6) == substr(PEPTIDE_INPUT, 6,6)) | (substr(peptable.peptide.subset, 7,7) == substr(PEPTIDE_INPUT, 7,7)) | (substr(peptable.peptide.subset, 8,8) == substr(PEPTIDE_INPUT, 8,8)))]
cat(paste(" Calculating", length(peptable.peptide.subset)," scores. This may take a few minutes\n"))
quarter_count = floor(length(peptable.peptide.subset)/4)
mod_count = length(peptable.peptide.subset) %% 4
TEST_Scores.filter_1 = sapply(peptable.peptide.subset[1:quarter_count],function(X) as.numeric(Get_Peptide_Scores(PEPTIDE_INPUT, X)))
cat(paste(" Calculating", (length(peptable.peptide.subset)-quarter_count)," scores. This may take a few minutes\n"))
TEST_Scores.filter_2 = sapply(peptable.peptide.subset[(quarter_count+1):(quarter_count*2)],function(X) as.numeric(Get_Peptide_Scores(PEPTIDE_INPUT, X)))
cat(paste(" Calculating", (length(peptable.peptide.subset)-quarter_count*2)," scores. This may take a few minutes\n"))
TEST_Scores.filter_3 = sapply(peptable.peptide.subset[(quarter_count*2 + 1):(quarter_count*3)],function(X) as.numeric(Get_Peptide_Scores(PEPTIDE_INPUT, X)))
cat(paste(" Calculating", (length(peptable.peptide.subset)-quarter_count*3)," scores. This may take a few minutes\n"))
TEST_Scores.filter_4 = sapply(peptable.peptide.subset[(quarter_count*3 + 1):length(peptable.peptide.subset)],function(X) as.numeric(Get_Peptide_Scores(PEPTIDE_INPUT, X)))
TEST_Scores.filter = c(TEST_Scores.filter_1,TEST_Scores.filter_2,TEST_Scores.filter_3,TEST_Scores.filter_4)
peptable$score = -100
cat(" Sorting Scores\n")
peptable$score[match(peptable.peptide.subset,as.character(peptable$peptide))] = TEST_Scores.filter
peptable$BindLevel = as.character(peptable$BindLevel)
peptable$BindLevel[which(peptable$BindLevel == "<= WB")] <- "Weak Binder"
peptable$BindLevel[which(peptable$BindLevel == "<= SB")] <- "Strong Binder"
}
Return_TOP = 100
colnames(peptable) <- c("Peptide", "Gene", "Affinity_(nM)","Bind_Level", "Peptide_Score")
peptable$Gene <- as.character(peptable$Gene)
peptable <- peptable[order(peptable$Peptide_Score, decreasing = T)[1: Return_TOP],]
peptable <- normal(peptable)
peptable <- ligandome(peptable)
peptable$Overall_Score = round(peptable$Peptide_Score * peptable$max_norm/peptable$'Affinity_(nM)',2)
Output_peptable = peptable[,c("Peptide","Gene","Peptide_Score","Overall_Score","Affinity_(nM)","max_norm","max_tissue","Normal_Ligandome","HLA")]
Output_peptable$max_tissue <- as.character(Output_peptable$max_tissue)
Output_peptable$max_norm <- round(as.numeric(Output_peptable$max_norm),2)
Output_peptable = Output_peptable[order(Output_peptable$Overall_Score,decreasing=T),]
rownames(Output_peptable) <- NULL
if(input_filetype == "csv")
{
write.csv(Output_peptable,Output_Path)
}
if(input_filetype == "tsv")
{
write.table(x = Output_peptable,file = Output_Path,quote = F,row.names = F,col.names = T,sep = "\t")
}
cat(paste(" Results are saved in ",out_file,"\n",sep=" "))
cat(" Job complete\n")
} #if(CHECKS) (end)