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nsaf_scoring.R |
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| diff -r e3625c710dd3 -r 2843d0da7f20 nsaf_scoring.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/nsaf_scoring.R Wed May 11 10:51:19 2016 -0400 |
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| @@ -0,0 +1,80 @@ +################################################################################################### +# R-code: APOSTL Global Variables +# Author: Brent Kuenzi + +################################################################################################### +# This program performs the file merging as well as a serious of calculations +# Following merging the following parameters will be calculated: +# 1) CRAPomePCT +# 2) NSAF +# 3) NSAFscore +# The resulting table will be exported. This is performed as its own tool and should not be used +# for input into the interactive analysis tool or the standalone bubble graph tool +################################## Dependencies ################################################### +library(dplyr); library(tidyr) +################################# Read in Data #################################################### +## REQUIRED INPUTS ## +## 1) listfile (filename) +#listfile <- "EGFR_list.txt" +## 2) Prey File (filename) +#preyfile <- "EGFR_prey.txt" +## 3) crapome File (filename or FALSE) +#crapfile <- "EGFR_crap.txt" +## 4) Inter File (filename) +#interfile <- "inter.txt" +################################# Create Table #################################################### +merge_files <- function(SAINT_DF, prey_DF, crapome=FALSE) { + SAINT <- read.table(SAINT_DF, sep='\t', header=TRUE) + prey <- read.table(prey_DF, sep='\t', header=FALSE); colnames(prey) <- c("Prey", "Length", "PreyGene") + DF <- merge(SAINT,prey) + + if(crapome!=FALSE) { + crapome <- read.table(crapome, sep='\t', header=TRUE) + colnames(crapome) <- c("Prey", "Symbol", "Num.of.Exp", "Ave.SC", "Max.SC") + DF1 <- merge(DF, crapome); as.character(DF1$Num.of.Exp); DF1$Symbol <- NULL; + DF1$Ave.SC <- NULL; DF1$Max.SC <- NULL #remove unnecessary columns + DF1$Num.of.Exp <- sub("^$", "0 / 1", DF1$Num.of.Exp ) #replace blank values with 0 / 1 + DF <- DF1 %>% separate(Num.of.Exp, c("NumExp", "TotalExp"), " / ") #split into 2 columns + DF$CrapomePCT <- round(100 - (as.integer(DF$NumExp) / as.integer(DF$TotalExp) * 100), digits=2) #calculate crapome % + + } + DF$FoldChange <- round(log2(DF$FoldChange),digits=2) + colnames(DF)[(colnames(DF)=="FoldChange")] <- "log2(FoldChange)" + + DF$SAF <- DF$AvgSpec / DF$Length + by_bait <- DF %>% group_by(Bait) %>% mutate("NSAF" = SAF/sum(SAF)) + by_bait$SAF <- NULL + return(by_bait[!duplicated(by_bait),]) +} + +main <- function(listfile, preyfile, crapfile, interfile) { + working <- as.data.frame(merge_files(listfile, preyfile, crapfile)) + inter_df <- read.table(interfile, sep='\t', header=FALSE) + working$temp <- strsplit(as.character(working$ctrlCounts),"[|]") + cnt <- 0 + for(i in working$temp){ + cnt <- cnt+1 + working$ctrl_mean[cnt] <- mean(as.numeric(unlist(i))) + working$ctrl_number[cnt] <- length(i)} + working$ctrl_SAF <- working$ctrl_mean / working$Length + main.data <- working %>% group_by(Bait) %>% mutate("control_NSAF" = ctrl_SAF/sum(ctrl_SAF)) + ctrl_SAF_constant <- 1/mean(main.data$ctrl_SAF) + # add ctrl_SAF_constant to prevent dividing by 0 + cnt <- 0 + for(i in main.data$control_NSAF){ + cnt <- cnt + 1 + main.data$nsafScore[cnt] <- ((main.data$NSAF[cnt])+ctrl_SAF_constant)/((i/main.data$ctrl_number[cnt])+ctrl_SAF_constant) + } + main.data$NSAF <- log(main.data$NSAF) + main.data$nsafScore <- log(main.data$nsafScore) + main.data <- filter(main.data, NSAF > -Inf) + colnames(main.data)[colnames(main.data)=="NSAF"] <- "ln(NSAF)" + colnames(main.data)[colnames(main.data)=="nsafScore"] <- "NSAFScore" + main.data$SAF <- NULL; main.data$ctrl_SAF <- NULL + main.data$control_NSAF <- NULL; main.data$temp <- NULL + main.data$ctrl_mean <- NULL + write.table(main.data,file="SaintTable.txt",sep="\t",row.names=FALSE,quote=FALSE) +} + +args <- commandArgs(trailingOnly = TRUE) +main(args[1], args[2], args[3], args[4]) |