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hartman-server/workflow/apps/r/joinInteractExps.R

234 lines
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R

#!/usr/bin/env Rscript
# JoinInteractExps.R
library(plyr)
library(sos)
library(dplyr)
args <- commandArgs(TRUE)
# Set output dir
if (length(args) >= 1) {
outDir <- file.path(args[1])
} else {
outDir <- "./" # for legacy workflow
}
# Set sd value
if (length(args) >= 2) {
sd <- args[2]
} else {
sd <- 2 # default value
}
print(paste("SD=", sd))
# Set studyInfo file
if (length(args) >= 3) {
studyInfo <- file.path(args[3])
} else {
studyInfo <- "../Code/StudyInfo.csv" # for legacy workflow
}
studies <- args[3:length(args)]
inputFiles <- c()
for (study in 1:length(studies)) {
zsFile <- file.path(study, "zscores", "zscores_interaction.csv")
if (file.exists(zsFile)) {
inputFiles[study] <- zsFile
}
}
print(length(inputFiles))
# TODO this is better handled in a loop in case you want to compare more experiments?
# The input is already designed for this
# Read in the files for your experiment and
# Join the two files at a time as a function of how many inputFile
# list the larger file first ? in this example X2 has the larger number of genes
# If X1 has a larger number of genes, switch the order of X1 and X2
if (length(inputFiles) == 2) {
X1 <- read.csv(file = inputFiles[1], stringsAsFactors = FALSE)
X2 <- read.csv(file = inputFiles[2], stringsAsFactors = FALSE)
X <- join(X1, X2, by = "OrfRep")
OBH <- X[, order(colnames(X))] # OrderByHeader
headSel <- select(OBH, contains("OrfRep"), matches("Gene"),
contains("Z_lm_K"), contains("Z_Shift_K"), contains("Z_lm_L"), contains("Z_Shift_L"))
headSel <- select(headSel, -"Gene.1") #remove "Gene.1 column
headSel2 <- select(OBH, contains("OrfRep"), matches("Gene")) #Frame for interleaving Z_lm with Shift colums
headSel2 <- select(headSel2, -"Gene.1") #remove "Gene.1 column #Frame for interleaving Z_lm with Shift colums
} else if (length(inputFiles) == 3) {
X1 <- read.csv(file = inputFiles[1], stringsAsFactors = FALSE) #exp1File,stringsAsFactors = FALSE)
X2 <- read.csv(file = inputFiles[2], stringsAsFactors = FALSE) #exp2File,stringsAsFactors = FALSE)
X3 <- read.csv(file = inputFiles[3], stringsAsFactors = FALSE) #exp3File,stringsAsFactors = FALSE)
X <- join(X1, X2, by = "OrfRep")
X <- join(X, X3, by = "OrfRep")
OBH <- X[, order(colnames(X))] #OrderByHeader
headSel <- select(OBH, contains("OrfRep"), matches("Gene"),
contains("Z_lm_K"), contains("Z_Shift_K"), contains("Z_lm_L"), contains("Z_Shift_L"))
headSel <- select(headSel, -"Gene.1", -"Gene.2")
headSel2 <- select(OBH, contains("OrfRep"), matches("Gene"))
headSel2 <- select(headSel2, -"Gene.1", -"Gene.2")
} else if (length(inputFiles) == 4) {
X1 <- read.csv(file = inputFiles[1], stringsAsFactors = FALSE) #exp1File,stringsAsFactors = FALSE)
X2 <- read.csv(file = inputFiles[2], stringsAsFactors = FALSE) #exp2File,stringsAsFactors = FALSE)
X3 <- read.csv(file = inputFiles[3], stringsAsFactors = FALSE) #exp3File,stringsAsFactors = FALSE)
X4 <- read.csv(file = inputFiles[4], stringsAsFactors = FALSE) #exp4File,stringsAsFactors = FALSE)
X <- join(X1, X2, by = "OrfRep")
X <- join(X, X3, by = "OrfRep")
X <- join(X, X4, by = "OrfRep")
OBH <- X[, order(colnames(X))] #OrderByHeader
headSel <- select(OBH, contains("OrfRep"), matches("Gene"),
contains("Z_lm_K"), contains("Z_Shift_K"), contains("Z_lm_L"), contains("Z_Shift_L"))
headSel <- select(headSel, -"Gene.1", -"Gene.2", -"Gene.3")
headSel2 <- select(OBH, contains("OrfRep"), matches("Gene"))
headSel2 <- select(headSel2, -"Gene.1", -"Gene.2", -"Gene.3")
}
# headSel$contains("Z_Shift") %>% replace_na(0.001)
headers <- colnames(headSel)
i <- 0
for (i in 1:length(headers)) {
if (grepl("Shift", headers[i])) {
headSel[headers[i]][is.na(headSel[headers[i]])] <- 0.001
}
if (grepl("Z_lm_", headers[i])) {
headSel[headers[i]][is.na(headSel[headers[i]])] <- 0.0001
}
}
# 2SD option code to exclude Z_lm values less than 2 standard Deviations
REMcRdy <- select(headSel, contains("OrfRep"), matches("Gene"), contains("Z_lm_"))
shiftOnly <- select(headSel, contains("OrfRep"), matches("Gene"), contains("Z_Shift"))
# Code to replace the numeric (.1 .2 .3) headers with experiment names from StudyInfo.txt
Labels <- read.csv(file = "../Code/StudyInfo.csv", stringsAsFactors = FALSE, sep = ",")
# Using Text search grepl to relabel headers
REMcRdyHdr <- colnames(REMcRdy)
REMcRdyLabels <- "asdf"
shftHdr <- colnames(shiftOnly)
shiftLabels <- "asdf"
shiftLabels[1:2] <- shftHdr[1:2]
REMcRdyLabels[1:2] <- REMcRdyHdr[1:2]
for (i in 3:(length(shftHdr))) {
if (i == 3) {
shiftLabels[3] <- paste0(Labels[1, 2], ".", shftHdr[3])
REMcRdyLabels[3] <- paste0(Labels[1, 2], ".", REMcRdyHdr[3])
}
if (i == 5) {
shiftLabels[5] <- paste0(Labels[1, 2], ".", shftHdr[5])
REMcRdyLabels[5] <- paste0(Labels[1, 2], ".", REMcRdyHdr[5])
}
if (i == 7) {
shiftLabels[7] <- paste0(Labels[1, 2], ".", shftHdr[7])
REMcRdyLabels[7] <- paste0(Labels[1, 2], ".", REMcRdyHdr[7])
}
if (grepl(".1", shftHdr[i], fixed = true)) {
shiftLabels[i] <- paste0(Labels[2, 2], ".", shftHdr[i])
REMcRdyLabels[i] <- paste0(Labels[2, 2], ".", REMcRdyHdr[i])
}
if (grepl(".2", shftHdr[i], fixed = true)) {
shiftLabels[i] < -paste0(Labels[3, 2], ".", shftHdr[i])
REMcRdyLabels[i] <- paste0(Labels[3, 2], ".", REMcRdyHdr[i])
}
if (grepl(".3", shftHdr[i], fixed = true)) {
shiftLabels[i] <- paste0(Labels[4, 2], ".", shftHdr[i])
REMcRdyLabels[i] <- paste0(Labels[4, 2], ".", REMcRdyHdr[i])
}
}
for (i in 3:(length(REMcRdyLabels))) {
j <- as.integer(i)
REMcRdyLabels[j] <- gsub("[.]", "_", REMcRdyLabels[j])
shiftLabels[j] <- gsub("[.]", "_", shiftLabels[j])
}
colnames(shiftOnly) <- shiftLabels
colnames(REMcRdy) <- REMcRdyLabels
combI <- headSel2 # starting Template orf, Genename columns
# headersRemc<-colnames(REMcRdy)
# Reorder columns to produce an interleaved set of Z_lm and Shift data for all the cpps.
for (i in 3:length(colnames(REMcRdy))) {
combI <- cbind.data.frame(combI, shiftOnly[i])
combI <- cbind.data.frame(combI, REMcRdy[i])
}
Vec1 <- NA
Vec2 <- NA
Vec3 <- NA
Vec4 <- NA
Vec5 <- NA
Vec6 <- NA
Vec7 <- NA
Vec8 <- NA
if (length(REMcRdy) == 6) {
Vec1 <- abs(REMcRdy[, 3]) >= std
Vec2 <- abs(REMcRdy[, 4]) >= std
Vec3 <- abs(REMcRdy[, 5]) >= std
Vec4 <- abs(REMcRdy[, 6]) >= std
bolVec <- Vec1 | Vec2 | Vec3 | Vec4
REMcRdyGT2 <- REMcRdy[bolVec, 1:2]
REMcRdyGT2[, 3:6] <- REMcRdy[bolVec, 3:6]
shiftOnlyGT2 <- shiftOnly[bolVec, 1:2]
shiftOnlyGT2[, 3:6] <- shiftOnly[bolVec, 3:6]
}
if (length(REMcRdy) == 8) {
Vec1 <- abs(REMcRdy[, 3]) >= std
Vec2 <- abs(REMcRdy[, 4]) >= std
Vec3 <- abs(REMcRdy[, 5]) >= std
Vec4 <- abs(REMcRdy[, 6]) >= std
Vec5 <- abs(REMcRdy[, 7]) >= std
Vec6 <- abs(REMcRdy[, 8]) >= std
bolVec <- Vec1 | Vec2 | Vec3 | Vec4 | Vec5 | Vec6
REMcRdyGT2 <- REMcRdy[bolVec, 1:2]
REMcRdyGT2[, 3:8] <- REMcRdy[bolVec, 3:8]
shiftOnlyGT2 <- shiftOnly[bolVec, 1:2]
shiftOnlyGT2[, 3:8] <- shiftOnly[bolVec, 3:8]
}
if (length(REMcRdy) == 10) {
Vec1 <- abs(REMcRdy[, 3]) >= std
Vec2 <- abs(REMcRdy[, 4]) >= std
Vec3 <- abs(REMcRdy[, 5]) >= std
Vec4 <- abs(REMcRdy[, 6]) >= std
Vec5 <- abs(REMcRdy[, 7]) >= std
Vec6 <- abs(REMcRdy[, 8]) >= std
Vec7 <- abs(REMcRdy[, 9]) >= std
Vec8 <- abs(REMcRdy[, 10]) >= std
bolVec <- Vec1 | Vec2 | Vec3 | Vec4 | Vec5 | Vec6 | Vec7 | Vec8
REMcRdyGT2 <- REMcRdy[bolVec, 1:2]
REMcRdyGT2[, 3:10] <- REMcRdy[bolVec, 3:10]
shiftOnlyGT2 <- shiftOnly[bolVec, 1:2]
shiftOnlyGT2[, 3:10] <- shiftOnly[bolVec, 3:10]
}
if (std != 0) {
REMcRdy <- REMcRdyGT2 # [,2:length(REMcRdyGT2)]
shiftOnly <- shiftOnlyGT2 # [,2:length(shiftOnlyGT2)]
}
if (std == 0) {
REMcRdy <- REMcRdy # [,2:length(REMcRdy)]
shiftOnly <- shiftOnly # [,2:length(shiftOnly)]
}
# R places hidden "" around the header names. The following
# is intended to remove those quote so that the "" do not blow up the Java REMc.
# Use ,quote=F in the write.csv statement to fix R output file.
# write.csv(combI,file.path(outDir,"CombinedKLzscores.csv"), row.names = FALSE)
write.csv(REMcRdy, file.path(outDir, "REMcRdy_lm_only.csv"), row.names = FALSE, quote = FALSE)
write.csv(shiftOnly, file.path(outDir, "Shift_only.csv"), row.names = FALSE, quote = FALSE)
#LabelStd <- read.table(file="./parameters.csv",stringsAsFactors = FALSE,sep = ",")
LabelStd <- read.csv(file = studyInfo, stringsAsFactors = FALSE)
print(std)
LabelStd[, 4] <- as.numeric(std)
write.csv(LabelStd, file = file.path(outDir, "parameters.csv"), row.names = FALSE)
write.csv(LabelStd, file = studyInfo, row.names = FALSE)