Rollup

.gitignore

@@ -2,3 +2,4 @@ old/
 manual.odt
 mwe
 centos-upgrade-plan.txt
+workflow/out/

workflow/README.md

@@ -34,6 +34,7 @@ Insert a general description of Q-HTCP and the Q-HTCP process here.
 * [py_gtf_concat](#pygtfconcat)
 * [r_compile_gtf](#rcompilegtf)
 * [get_studies](#getstudies)
+* [choose_easy_results](#chooseeasyresults)
 
 ## Notes
 
@@ -94,7 +95,7 @@ Insert a general description of Q-HTCP and the Q-HTCP process here.
 
 ### parse_input
 
-`--project`, `--module`, `--nomodule`, and `--submodule` can be passed multiple times or with a comma-separated string
+`--project`, `--module`, `--nomodule`, and `--wrapper` can be passed multiple times or with a comma-separated string
 
 #### Options
 
@@ -106,9 +107,9 @@ Insert a general description of Q-HTCP and the Q-HTCP process here.
 
   One or more modules to run (default: all), can be passed multiple times or with a comma-separated string
 
-* **-s\<value\>** | **--submodule=\<value\>**
+* **-w\<value\>** | **--wrapper=\<value\>**
 
-  Requires two arguments: the name of the submodule and its arguments, can be passed multiple times
+  Requires two arguments: the name of the wrapper and its arguments, can be passed multiple times
 
 * **-n\<value\>** | **--nomodule=\<value\>**
 
@@ -134,7 +135,7 @@ Insert a general description of Q-HTCP and the Q-HTCP process here.
 
 * **PROJECTS** (array): List of projects to cycle through
 * **MODULES** (array): List of modules to run on each project
-* **SUBMODULES** (array): List of submodules and their arguments to run on each project
+* **WRAPPERS** (array): List of wrappers and their arguments to run on each project
 * **EXCLUDE_MODULES** (array): List of modules not to run on each project
 * **DEBUG** (int): Turn debugging on
 * **YES** (int): Turn assume yes on
@@ -147,10 +148,10 @@ Use a module to:
 
 * Build a new type of analysis from scratch
 * Generate project directories
-* Group multiple submodules (and modules) into a larger task
+* Group multiple wrappers (and modules) into a larger task
-* Dictate the ordering of multiple submodules
+* Dictate the ordering of multiple wrappers
-* Competently handle pushd and popd for their submodules if they do not reside in the SCANS/PROJECT_DIR
+* Competently handle pushd and popd for their wrappers if they do not reside in the SCANS/PROJECT_DIR
-* Call their submodules with the appropriate arguments
+* Call their wrappers with the appropriate arguments
 
 ### install_dependencies
 
@@ -204,6 +205,7 @@ TODO
 * MasterPlate_ file **should not be an xlsx file**, no portability
 * We can keep the existing xlsx code for old style fallback
 * But moving forward should switch to csv or something open
+* Do we need to sync a QHTCP template?
 
 NOTES
 
@@ -218,6 +220,15 @@ NOTES
 
 Run the EASY matlab program
 
+INPUT FILES
+* MasterPlate_.xls
+* DrugMedia_.xls
+
+OUTPUT FILES
+* !!ResultsStd_.txt
+* !!ResultsELr_.txt
+
+
 TODO
 
 * Don't create output in the scans folder, put it in an output directory
@@ -612,11 +623,9 @@ TODO
 * **$5** (string): All_SGD_GOTerms_for_QHTCPtk.csv
 * **$6** (string): zscores_interaction.csv
 
-## Submodules
+## Wrappers
 
-Submodules are shell wrappers for workflow components in external languages
+Wrappers:
-
-Submodules:
 
 * Allow scripts to be called by the main workflow script using input and output arguments as a translation mechanism.
 * Only run by default if called by a module.
@@ -665,7 +674,7 @@ Output
 
 *
 
-This submodule:
+This wrapper:
 
 * Will perform both L and K comparisons for the specified experiment folders. 
 * The code uses the naming convention of PairwiseCompare_Exp’#’-Exp’#’ to standardize and keep simple the structural naming (where ‘X’ is either K or L and ‘Y’ is the number of the experiment GTA results to be found in ../GTAresult/Exp_).
@@ -697,7 +706,7 @@ Output
 
 *
 
-This submodule:
+This wrapper:
 
 * The Term Specific Heatmaps are produced directly from the ../ExpStudy/Exp_/ZScores/ZScores_Interaction.csv file generated by the user modified interaction… .R  script. 
 * The heatmap labeling is per the names the user wrote into the StudyInfo.txt spreadsheet.
@@ -716,11 +725,18 @@ This submodule:
 
 ### r_interactions
 
-Run the R interactions analysis (Z_InteractionTemplate.R)
+Run the R interactions analysis (deprecates Z_InteractionTemplate.R)
+
+SCRIPT: interactions.R
 
 TODO
 
-* Don't want to rename Z_InteractionTemplate.R because that will break logic, just edit in place instead
+* Parallelization (need to consult with Sean)
+* Needs more loops to reduce verbosity, but don't want to limit flexibility
+* Replace 1:length() with seq_along()
+* Re-enable disabled linter checks
+* Reduce cyclomatic complexity of some of the for loops
+* There needs to be one point of truth for the SD factor
 
 NOTES
 
@@ -729,10 +745,11 @@ NOTES
 #### Arguments
 
 * **$1** (string): The input directory
-* **$2** (string): The study info file
+* **$2** (string): The zscores directory
-* **$3** (string): The zscores directory
+* **$3** (string): The study info file
 * **$4** (string): SGD_features.tab
 * **$5** (integer): delta SD background value (default: 5)
+* **$6** (integer): experiment number
 
 ### r_join_interactions
 
@@ -826,7 +843,7 @@ Output
 
 ### pl_gtf_analyze
 
-Perl analyze submodule
+Perl analyze wrapper
 This seems weird to me because we're just overwriting the same data for all set2 members
 https://metacpan.org/dist/GO-TermFinder/view/examples/analyze.pl
 Is there a reason you need a custom version and not the original from cpan?
@@ -840,7 +857,7 @@ Is there a reason you need a custom version and not the original from cpan?
 
 ### pl_gtf_terms2tsv
 
-Perl terms2tsv submodule
+Perl terms2tsv wrapper
 Probably should be translated to shell/python
 
 #### Arguments
@@ -849,7 +866,7 @@ Probably should be translated to shell/python
 
 ### py_gtf_concat
 
-Python concat submodule for GTF
+Python concat wrapper for GTF
 Concat the process ontology outputs from the /REMcReady_lm_only folder
 Probably should be translated to bash
 
@@ -872,14 +889,14 @@ Parse study names from StudyInfo.csv files
 
 TODO
 
-* This whole submodule should eventually be either
+* This whole wrapper should eventually be either
 * Removed
 * Expanded into a file that stores all project/study settings (database)
 * I had to had a new line to the end of StudyInfo.csv, may break things?
 
 #### Arguments
 
-* **$1** (string): File to read
+* **$1** (string): Study info file
 
 #### Variables set
 
@@ -890,3 +907,21 @@ TODO
 * **0**: If one or more studies found
 * **1**: If no studies found
 
+### choose_easy_results
+
+Chooses an EASY scans directory if the information is undefined
+TODO Standardize EASY output, it's hard to understand
+TODO eventually we could run this on multiple results dirs simultaneously with some refactoring
+
+#### Arguments
+
+* **$1** (string): directory containing EASY results dirs
+
+#### Variables set
+
+* **EASY_RESULTS_DIR** (string): The working EASY output directory
+
+#### Exit codes
+
+* **0**: if successfully choose anEASY results dir
+

workflow/apps/r/addShiftVals.R

@@ -7,7 +7,7 @@ library(plyr)
 library(dplyr)
 library(sos)
 
-args=commandArgs(TRUE)
+args <- commandArgs(TRUE)
 
 if (length(args) >= 1) {
   finalTable <- args[1]
@@ -33,59 +33,58 @@ if (length(args) >= 4) {
   output <- "REMcHeatmaps/REMcWithShift.csv" # for legacy workflow
 }
 
-
 # Read in the REMc finalTable data
-X = data.frame(read.csv(file=finalTable,header=TRUE,stringsAsFactors = FALSE))
+X <- data.frame(read.csv(file = finalTable, header = TRUE, stringsAsFactors = FALSE))
 # Read in the shift data From ../JoinInteractions
-Y = data.frame(read.csv(file=shiftFile,header=TRUE,stringsAsFactors = FALSE))
+Y <- data.frame(read.csv(file = shiftFile, header = TRUE, stringsAsFactors = FALSE))
-Labels <- read.delim(studyInfo,skip=0,as.is=T,row.names=1,strip.white=TRUE)
+Labels <- read.delim(studyInfo, skip = 0, as.is = TRUE, row.names = 1, strip.white = TRUE)
 
 # Determine the number of cols - needed to create the correct number of new cols
 Xcolnum <- length(X[1, ])
 ADDnum <- Xcolnum + length(Y[1, ]) - 2
 
 # Create new columns filled with NAs to be filled with data
-Xtemp= X
+Xtemp <- X
 Xtemp[, (Xcolnum + 1):ADDnum] <- NA
 
 # Match the orf names in each row to a orf name in the shift data file and then add the shift data to the finalTable file
 shiftTbl < - as.data.frame(matrix(nrow = 1, ncol = length(Y) - 2)) #the df shiftTbl must be initialized before for loop
 
 for (i in 1:length(X[, 1])) {
-  Shiftrownum = match(X[i,2],Y[,1])
+  Shiftrownum <- match(X[i, 2], Y[, 1])
-  shiftTbl[i,]= Y[Shiftrownum,3:length(Y[1,])]
+  shiftTbl[i, ] <- Y[Shiftrownum, 3:length(Y[1, ])]
   Xtemp[i, (Xcolnum + 1):ADDnum] <- Y[Shiftrownum, 3:length(Y[1, ])]
 }
-headerX= colnames(Xtemp)
+headerX <- colnames(Xtemp)
-headerY= colnames(Y)
+headerY <- colnames(Y)
-shfHdr= headerY[3:length(headerY)]
+shfHdr <- headerY[3:length(headerY)]
 combTbl <- X[, 1:3]
-lmTbl= select(Xtemp,  contains('Z_lm'))  #X[,(4:Xcolnum-2)]
+lmTbl <- select(Xtemp,  contains("Z_lm"))  #X[,(4:Xcolnum-2)]
-shiftTbl<- select(Xtemp,  contains('V'))
+shiftTbl <- select(Xtemp,  contains("V"))
-clustTbl<- select(Xtemp, contains('cluster.'))
+clustTbl <- select(Xtemp, contains("cluster."))
 
 # Give the new column names the same names as in the shift file
-Xcols = colnames(X)
+Xcols <- colnames(X)
-Ycols = colnames(Y)[3:length(Y[1,])]
+Ycols <- colnames(Y)[3:length(Y[1, ])]
-newCols = c(Xcols[1:Xcolnum],Ycols)
+newCols <- c(Xcols[1:Xcolnum], Ycols)
 
 # Reorder columns for generating heatmaps
-combI= combTbl  #Starting Template orf, Genename columns
+combI <- combTbl  #Starting Template orf, Genename columns
 headersRemc <- newCols  #colnames(X)
-newHeaders= newCols[1:3]
+newHeaders <- newCols[1:3]
-lmHdr= colnames(lmTbl)   #newCols[4:(length(Xcols)-2)]
+lmHdr <- colnames(lmTbl)   #newCols[4:(length(Xcols)-2)]
-clstHdr= colnames(clustTbl)  #select(newCols, contains('cluster.'))  #newCols[3+length(lmHdr):2]
+clstHdr <- colnames(clustTbl)  #select(newCols, contains('cluster.'))  #newCols[3+length(lmHdr):2]
 
-intLvHdr= vector()
+intLvHdr <- vector()
 #Reorder columns to produce an interleaved set of Z_lm and Shift data for all the cpps.
 for (i in 1:(length(shiftTbl[1, ]))) {
-  combI=cbind.data.frame(combI, shiftTbl[i])
+  combI <- cbind.data.frame(combI, shiftTbl[i])
-  combI=cbind.data.frame(combI, lmTbl[i])
+  combI <- cbind.data.frame(combI, lmTbl[i])
-  intLvHdrx= c(shfHdr[i],lmHdr[i] )
+  intLvHdrx <- c(shfHdr[i], lmHdr[i])
-  intLvHdr= c(intLvHdr,intLvHdrx)
+  intLvHdr <- c(intLvHdr, intLvHdrx)
 }
 
-combIHdr= c(colnames(combTbl),intLvHdr,clstHdr)
+combIHdr <- c(colnames(combTbl), intLvHdr, clstHdr)
-combI=cbind.data.frame(combI, clustTbl)
+combI <- cbind.data.frame(combI, clustTbl)
-colnames(combI)= combIHdr
+colnames(combI) <- combIHdr
 write.csv(combI, file = output, row.names = FALSE)

workflow/apps/r/createHeatMaps.R

@@ -9,13 +9,13 @@ args <- commandArgs(TRUE)
 
 # Set output dir
 if (length(args) >= 1) {
-  input_finalTable <- args[1]
+  input_finalTable <- file.path(args[1])
 } else {
   input_finalTable <- "/REMcHeatmaps/REMcWithShift.csv" # for legacy workflow
 }
 
 if (length(args) >= 2) {
-  outDir <- args[2]
+  outDir <- file.path(args[2])
 } else {
   outDir <- "/REMcHeatmaps/REMcWithShift.csv" # for legacy workflow
 }
@@ -31,11 +31,12 @@ hmapfile[hmapfile == -0.001] <- NA
 num_total_genes <- length(hmapfile[, 1])
 
 # Break out the cluster names so each part of the cluster origin can be accessed
-# line below removed because it adds to many genes to clusters when going past 1-0-10 since it cannot differentiate between 1-0-1 and 1-0-10 when using grepl.
+# line below removed because it adds to many genes to clusters when going past 1-0-10
+# since it cannot differentiate between 1-0-1 and 1-0-10 when using grepl.
 # hmapfile$cluster.origin = gsub(" ","",x=hmapfile$cluster.origin)
 
-hmapfile$cluster.origin = gsub(";"," ;",x=hmapfile$cluster.origin)
+hmapfile$cluster.origin <- gsub(";", " ;", x = hmapfile$cluster.origin)
-hmapfile$cluster.origin = strsplit(hmapfile$cluster.origin,';')
+hmapfile$cluster.origin <- strsplit(hmapfile$cluster.origin, ";")
 #use tail(x,n) for accessing the outward most cluster
 
 clust_rounds <- 0
@@ -54,7 +55,8 @@ num_unique_clusts <- length(unique_clusts)
 
 # Base the color key on a statistical analysis of the L and K data
 # need to create "breaks" to set the color key, need to have 12 different breaks (for 11 colors)
-# scale() will calculate the mean and standard deviation of the entire vector, then "scale" each element by those values by subtracting the mean and dividing by the sd.
+# scale() will calculate the mean and standard deviation of the entire vector,
+# then "scale" each element by those values by subtracting the mean and dividing by the sd.
 # hmapfile[,4:(length(hmapfile[1,]) - 2)] <- scale(hmapfile[,4:(length(hmapfile[1,]) - 2)])
 # change so that the L data is multiplied to be on the same scale as the K data
 
@@ -101,12 +103,15 @@ print(KEY_MIN)
 print(L_MAX)
 # print(L_Multiplier)
 
-colormapbreaks <- c(KEY_MIN,KEY_MIN*(5/6),KEY_MIN*(4/6),KEY_MIN*(3/6),KEY_MIN*(2/6),KEY_MIN*(1/6),KEY_MAX*(1/6),KEY_MAX*(2/6),KEY_MAX*(3/6),KEY_MAX*(4/6),KEY_MAX*(5/6),KEY_MAX)
+colormapbreaks <- c(KEY_MIN, KEY_MIN * (5 / 6), KEY_MIN * (4 / 6), KEY_MIN * (3 / 6), KEY_MIN * (2 / 6),
+  KEY_MIN * (1 / 6), KEY_MAX * (1 / 6), KEY_MAX * (2 / 6), KEY_MAX * (3 / 6), KEY_MAX * (4 / 6), KEY_MAX * (5 / 6), KEY_MAX)
 # print(colormapbreaks)
 
 # Probably should give a way to detect shift in case that is is not in the first row... (maybe just grepl for the whole column name?)
-# However since also using this to amend the first part. Could possibly identify all the ones that contain the word shift and then create an object containing just those numbers
+# However since also using this to amend the first part.
-# then could just use these values and create spaces only between interaction values - possibly could get rid of redundant shift values if we don't want to view these
+# Could possibly identify all the ones that contain the word shift and then create an object containing just those numbers
+# then could just use these values and create spaces only between interaction values
+# possibly could get rid of redundant shift values if we don't want to view these
 # could we pool all the shift data/average it?
 if (grepl("Shift", colnames(hmapfile)[4], fixed = TRUE) == TRUE) {
   even_columns <- seq(from = 2, to = (length(hmapfile[1, ]) - 7), by = 2)
@@ -149,7 +154,6 @@ for(i in 1:length(colnames_edit)){
     # if(length(unlist(INT_store)) == 6){
     #   colnames_edit[i+1] <- paste(unlist(INT_store)[1],unlist(INT_store)[2],unlist(INT_store)[6],sep=" ")
     # }
-
   }
 }
 print(colnames_edit)
@@ -159,7 +163,6 @@ print(colnames_edit)
 # colnames_edit[15] <- "TEM HLEG L"
 # colnames_edit[20] <- "TEM HL L"
 
-
 # Create the heatmaps
 for (i in 1:num_unique_clusts) {
   cluster <- unique_clusts[i]
@@ -168,9 +171,10 @@ for(i in 1:num_unique_clusts){
   if (cluster_length != 1) {
     X0 <- as.matrix(cluster_data[, 4:(length(hmapfile[1, ]) - 2)])
     if (cluster_length >= 2001) {
-      mypath = file.path(outDir,paste("cluster_",gsub(" ","",cluster), ".pdf",sep=""))
+      mypath <- file.path(outDir, paste("cluster_", gsub(" ", "", cluster), sep = ""), ".pdf")
       pdf(file = mypath, height = 20, width = 15)
-      heatmap.2(x=X0,
+      heatmap.2(
+        x = X0,
         Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
         dendrogram = "row", cexCol = 0.8, cexRow = 0.1, scale = "none",
         breaks = colormapbreaks, symbreaks = FALSE, colsep = even_columns, sepcolor = "white", offsetCol = 0.1,
@@ -181,14 +185,16 @@ for(i in 1:num_unique_clusts){
         na.color = "red", col = brewer.pal(11, "PuOr"),
         main = cluster,
         # ColSideColors=ev_repeat,
-                labRow=as.character(cluster_data$Gene), labCol=colnames_edit)
+        labRow = as.character(cluster_data$Gene), labCol = colnames_edit
+      )
       # abline(v=0.5467,col="black")
       dev.off()
     }
     if (cluster_length >= 201 && cluster_length <= 2000) {
-      mypath = file.path(outDir,paste("cluster_",gsub(" ","",cluster), ".pdf",sep=""))
+      mypath <- file.path(outDir, paste("cluster_", gsub(" ", "", cluster), sep = ""), ".pdf")
       pdf(file = mypath, height = 15, width = 12)
-      heatmap.2(x=X0,
+      heatmap.2(
+        x = X0,
         Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
         dendrogram = "row", cexCol = 0.8, cexRow = 0.1, scale = "none",
         breaks = colormapbreaks, symbreaks = FALSE, colsep = even_columns, sepcolor = "white", offsetCol = 0.1,
@@ -198,14 +204,16 @@ for(i in 1:num_unique_clusts){
         keysize = 0.7, trace = "none", density.info = c("none"), margins = c(10, 8),
         na.color = "red", col = brewer.pal(11, "PuOr"),
         main = cluster,
-                labRow=as.character(cluster_data$Gene), labCol=colnames_edit)
+        labRow = as.character(cluster_data$Gene), labCol = colnames_edit
+      )
       # abline(v=0.5316,col="black")
       dev.off()
     }
     if (cluster_length >= 150 && cluster_length <= 200) {
-      mypath = file.path(outDir,paste("cluster_",gsub(" ","",cluster), ".pdf",sep=""))
+      mypath <- file.path(outDir, paste("cluster_", gsub(" ", "", cluster), sep = ""), ".pdf")
       pdf(file = mypath, height = 12, width = 12)
-      heatmap.2(x=X0,
+      heatmap.2(
+        x = X0,
         Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
         dendrogram = "row", cexCol = 0.8, cexRow = 0.1, scale = "none",
         breaks = colormapbreaks, symbreaks = FALSE, colsep = even_columns, sepcolor = "white", offsetCol = 0.1,
@@ -215,13 +223,15 @@ for(i in 1:num_unique_clusts){
         keysize = 1, trace = "none", density.info = c("none"), margins = c(10, 8),
         na.color = "red", col = brewer.pal(11, "PuOr"),
         main = cluster,
-                labRow=as.character(cluster_data$Gene), labCol=colnames_edit)
+        labRow = as.character(cluster_data$Gene), labCol = colnames_edit
+      )
       dev.off()
     }
     if (cluster_length >= 101 && cluster_length <= 149) {
-      mypath = file.path(outDir,paste("cluster_",gsub(" ","",cluster), ".pdf",sep=""))
+      mypath <- file.path(outDir, paste("cluster_", gsub(" ", "", cluster), sep = ""), ".pdf")
       pdf(file = mypath, mypath, height = 12, width = 12)
-      heatmap.2(x=X0,
+      heatmap.2(
+        x = X0,
         Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
         dendrogram = "row", cexCol = 0.8, cexRow = 0.2, scale = "none",
         breaks = colormapbreaks, symbreaks = FALSE, colsep = even_columns, sepcolor = "white", offsetCol = 0.1,
@@ -231,13 +241,15 @@ for(i in 1:num_unique_clusts){
         keysize = 1, trace = "none", density.info = c("none"), margins = c(10, 8),
         na.color = "red", col = brewer.pal(11, "PuOr"),
         main = cluster,
-                labRow=as.character(cluster_data$Gene), labCol=colnames_edit)
+        labRow = as.character(cluster_data$Gene), labCol = colnames_edit
+      )
       dev.off()
     }
     if (cluster_length >= 60 && cluster_length <= 100) {
-      mypath = file.path(outDir,paste("cluster_",gsub(" ","",cluster), ".pdf",sep=""))
+      mypath <- file.path(outDir, paste("cluster_", gsub(" ", "", cluster), sep = ""), ".pdf")
       pdf(file = mypath, height = 12, width = 12)
-      heatmap.2(x=X0,
+      heatmap.2(
+        x = X0,
         Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
         dendrogram = "row", cexCol = 0.8, cexRow = 0.4, scale = "none",
         breaks = colormapbreaks, symbreaks = FALSE, colsep = even_columns, sepcolor = "white", offsetCol = 0.1,
@@ -247,13 +259,15 @@ for(i in 1:num_unique_clusts){
         keysize = 1, trace = "none", density.info = c("none"), margins = c(10, 8),
         na.color = "red", col = brewer.pal(11, "PuOr"),
         main = cluster,
-                labRow=as.character(cluster_data$Gene), labCol=colnames_edit)
+        labRow = as.character(cluster_data$Gene), labCol = colnames_edit
+      )
       dev.off()
     }
     if (cluster_length <= 59 && cluster_length >= 30) {
-      mypath = file.path(outDir,paste("cluster_",gsub(" ","",cluster), ".pdf",sep=""))
+      mypath <- file.path(outDir, paste("cluster_", gsub(" ", "", cluster), sep = ""), ".pdf")
       pdf(file = mypath, height = 9, width = 12)
-      heatmap.2(x=X0,
+      heatmap.2(
+        x = X0,
         Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
         dendrogram = "row", cexCol = 0.8, cexRow = 0.6, scale = "none",
         breaks = colormapbreaks, symbreaks = FALSE, colsep = even_columns, sepcolor = "white", offsetCol = 0.1,
@@ -263,13 +277,15 @@ for(i in 1:num_unique_clusts){
         keysize = 1, trace = "none", density.info = c("none"), margins = c(10, 8),
         na.color = "red", col = brewer.pal(11, "PuOr"),
         main = cluster,
-                labRow=as.character(cluster_data$Gene), labCol=colnames_edit)
+        labRow = as.character(cluster_data$Gene), labCol = colnames_edit
+      )
       dev.off()
     }
     if (cluster_length <= 29) {
-      mypath = file.path(outDir,paste("cluster_",gsub(" ","",cluster), ".pdf",sep=""))
+      mypath <- file.path(outDir, paste("cluster_", gsub(" ", "", cluster), sep = ""), ".pdf")
       pdf(file = mypath, height = 7, width = 12)
-      heatmap.2(x=X0,
+      heatmap.2(
+        x = X0,
         Rowv = TRUE, Colv = NA,
         distfun = dist, hclustfun = hclust,
         dendrogram = "row", cexCol = 0.8, cexRow = 0.9, scale = "none",
@@ -280,7 +296,8 @@ for(i in 1:num_unique_clusts){
         keysize = 1, trace = "none", density.info = c("none"), margins = c(10, 8),
         na.color = "red", col = brewer.pal(11, "PuOr"),
         main = cluster,
-                labRow=as.character(cluster_data$Gene), labCol=colnames_edit)
+        labRow = as.character(cluster_data$Gene), labCol = colnames_edit
+      )
       dev.off()
     }
   }

workflow/apps/r/interactions.R

@@ -20,25 +20,25 @@ library(htmlwidgets)
 
 # Parse arguments
 args <- commandArgs(TRUE)
-inputFile <- args[1]
+inputFile <- file.path(args[1])
 
 # Set output dir
 if (length(args) >= 2) {
-  outDir <- args[2]
+  outDir <- file.path(args[2])
 } else {
   outDir <- "/ZScores/" # for legacy workflow
 }
 
 # Set StudyInfo file path
 if (length(args) >= 3) {
-  studyInfo <- args[3]
+  studyInfo <- file.path(args[3])
 } else {
   studyInfo <- "../Code/StudyInfo.csv" # for legacy workflow
 }
 
 # Set SGDgeneList file path
 if (length(args) >= 4) {
-  SGDgeneList <- args[4]
+  SGDgeneList <- file.path(args[4])
 } else {
   SGDgeneList <- "../Code/SGD_features.tab" # for legacy workflow
 }
@@ -54,7 +54,7 @@ if (length(args) >= 5) {
 }
 delBGFactor <- as.numeric(delBGFactor)
 if (is.na(delBGFactor)) {
-  delBGFactor <- 3 # Recommended by Sean
+  delBGFactor <- 3 # recommended by Sean
 }
 print(paste("The Standard Deviation Value is:", delBGFactor))
 
@@ -68,21 +68,25 @@ if (length(args) >= 6) {
 }
 expNumber <- as.numeric(expNumber)
 
-outDir_QC <- paste(outDir, "QC/", sep = "")
+outDir_QC <- file.path(outDir, "QC")
 
 if (!file.exists(outDir)) {
-  dir.create(file.path(outDir))
+  dir.create(outDir)
 }
 
 if (!file.exists(outDir_QC)) {
   dir.create(file.path(outDir_QC))
 }
 
-# Capture Exp_ number, use it to Save args[2]{std}to Labels field and then
+options(width = 1000)
-# write to Labels to studyInfo.txt for future reference
+ls.str()
-Labels <- read.csv(file = studyInfo, stringsAsFactors = FALSE)  # sep = ","
+
-Labels[expNumber, 3] <- delBGFactor
+# Write delBJFactor to the StudyInfo file
-write.csv(Labels, file = studyInfo, row.names = FALSE)
+# TODO we probably shouldn't be doing this, need one source of truth
+# TODO disabling this for now
+# Labels <- read.csv(file = studyInfo, stringsAsFactors = FALSE)  # sep = ","
+# Labels[expNumber, 3] <- delBGFactor
+# write.csv(Labels, file = studyInfo, row.names = FALSE)
 
 # Begin User Data Selection Section
 
@@ -366,19 +370,19 @@ Raw_l_vs_K_beforeQC <-
   ggtitle("Raw L vs K before QC") +
   theme_publication_legend_right()
 
-pdf(paste(outDir_QC, "Raw_L_vs_K_beforeQC.pdf", sep = ""), width = 12, height = 8)
+pdf(file.path(outDir_QC, "Raw_L_vs_K_beforeQC.pdf"), width = 12, height = 8)
 Raw_l_vs_K_beforeQC
 
 dev.off()
 
 pgg <- ggplotly(Raw_l_vs_K_beforeQC)
-plotly_path <- paste(outDir_QC, "Raw_L_vs_K_beforeQC.html", sep = "")
+plotly_path <- file.path(outDir_QC, "Raw_L_vs_K_beforeQC.html")
 saveWidget(pgg, file = plotly_path, selfcontained = TRUE)
 
 # Set delta background tolerance based on 3 sds from the mean delta background
 Delta_Background_Tolerance <- mean(X$Delta_Backgrd) + (delBGFactor * sd(X$Delta_Backgrd))
 # Delta_Background_Tolerance <- mean(X$Delta_Backgrd)+(3*sd(X$Delta_Backgrd))
-print(paste("Delta_Background_Tolerance is", Delta_Background_Tolerance, sep = " "))
+sprintf("Delta_Background_Tolerance is %f", Delta_Background_Tolerance)
 
 Plate_Analysis_Delta_Backgrd <-
   ggplot(X, aes(Scan, Delta_Backgrd, color = as.factor(Conc_Num))) +
@@ -417,13 +421,13 @@ X_Delta_Backgrd_above_Tolerance_L_vs_K <-
   ) +
   theme_publication_legend_right()
 
-pdf(paste(outDir_QC, "Raw_L_vs_K_for_strains_above_deltabackgrd_threshold.pdf", sep = ""), width = 12, height = 8)
+pdf(file.path(outDir_QC, "Raw_L_vs_K_for_strains_above_deltabackgrd_threshold.pdf"), width = 12, height = 8)
 X_Delta_Backgrd_above_Tolerance_L_vs_K
 
 dev.off()
 
 pgg <- ggplotly(X_Delta_Backgrd_above_Tolerance_L_vs_K)
-plotly_path <- paste(outDir_QC, "Raw_L_vs_K_for_strains_above_deltabackgrd_threshold.html", sep = "")
+plotly_path <- file.path(outDir_QC, "Raw_L_vs_K_for_strains_above_deltabackgrd_threshold.html")
 saveWidget(pgg, file = plotly_path, selfcontained = TRUE)
 
 # Frequency plot for all data vs. the delta_background
@@ -434,7 +438,7 @@ DeltaBackground_Frequency_Plot <- ggplot(X, aes(Delta_Backgrd, color = as.factor
 DeltaBackground_Bar_Plot <- ggplot(X, aes(Delta_Backgrd, color = as.factor(Conc_Num))) + geom_bar() +
   ggtitle("Bar plot for Delta Background by Conc All Data") + theme_publication_legend_right()
 
-pdf(file = paste(outDir_QC, "Frequency_Delta_Background.pdf", sep = ""), width = 12, height = 8)
+pdf(file.path(outDir_QC, "Frequency_Delta_Background.pdf"), width = 12, height = 8)
 print(DeltaBackground_Frequency_Plot)
 print(DeltaBackground_Bar_Plot)
 dev.off()
@@ -568,7 +572,7 @@ Plate_Analysis_Delta_Backgrd_Box_afterQC <-
   theme_publication()
 
 # Print the plate analysis data before and after QC
-pdf(file = paste(outDir_QC, "Plate_Analysis.pdf", sep = ""), width = 14, height = 9)
+pdf(file.path(outDir_QC, "Plate_Analysis.pdf"), width = 14, height = 9)
 Plate_Analysis_L
 Plate_Analysis_L_afterQC
 Plate_Analysis_K
@@ -582,7 +586,7 @@ Plate_Analysis_Delta_Backgrd_afterQC
 dev.off()
 
 # Print the plate analysis data before and after QC
-pdf(file = paste(outDir_QC, "Plate_Analysis_Boxplots.pdf", sep = ""), width = 18, height = 9)
+pdf(file.path(outDir_QC, "Plate_Analysis_Boxplots.pdf"), width = 18, height = 9)
 Plate_Analysis_L_Box
 Plate_Analysis_L_Box_afterQC
 Plate_Analysis_K_Box
@@ -713,7 +717,7 @@ Plate_Analysis_Delta_Backgrd_Box_afterQC_Z <-
   theme_publication()
 
 # Print the plate analysis data before and after QC
-pdf(file = paste(outDir_QC, "Plate_Analysis_noZeros.pdf", sep = ""), width = 14, height = 9)
+pdf(file.path(outDir_QC, "Plate_Analysis_noZeros.pdf"), width = 14, height = 9)
 Plate_Analysis_L_afterQC_Z
 Plate_Analysis_K_afterQC_Z
 Plate_Analysis_r_afterQC_Z
@@ -722,7 +726,7 @@ Plate_Analysis_Delta_Backgrd_afterQC_Z
 dev.off()
 
 # Print the plate analysis data before and after QC
-pdf(file = paste(outDir_QC, "Plate_Analysis_noZeros_Boxplots.pdf", sep = ""), width = 18, height = 9)
+pdf(file.path(outDir_QC, "Plate_Analysis_noZeros_Boxplots.pdf"), width = 18, height = 9)
 Plate_Analysis_L_Box_afterQC_Z
 Plate_Analysis_K_Box_afterQC_Z
 Plate_Analysis_r_Box_afterQC_Z
@@ -768,7 +772,7 @@ X_stats_ALL <- ddply(
 )
 
 # print(X_stats_ALL_L)
-write.csv(X_stats_ALL, file = paste(outDir, "SummaryStats_ALLSTRAINS.csv"), row.names = FALSE)
+write.csv(X_stats_ALL, file.path(outDir, "SummaryStats_ALLSTRAINS.csv"), row.names = FALSE)
 
 # Part 3 - Generate summary statistics and calculate the max theoretical L value
 # Calculate the Z score at each drug conc for each deletion strain
@@ -885,7 +889,7 @@ for (s in Background_Strains) {
     se_AUC = sd_AUC / sqrt(N - 1)
   )
   
-  write.csv(X_stats_BY, file = paste(outDir, "SummaryStats_BackgroundStrains.csv"), row.names = FALSE)
+  write.csv(X_stats_BY, file.path(outDir, "SummaryStats_BackgroundStrains.csv"), row.names = FALSE)
   
   # Calculate the max theoretical L values
   # Only look for max values when K is within 2SD of the ref strain
@@ -964,7 +968,7 @@ for (s in Background_Strains) {
 
   write.csv(
     X_stats_BY_L_within_2SD_K,
-    file = paste(outDir_QC, "Max_Observed_L_Vals_for_spots_within_2SD_K.csv", sep = ""),
+    file.path(outDir_QC, "Max_Observed_L_Vals_for_spots_within_2SD_K.csv"),
     row.names = FALSE
   )
   
@@ -991,13 +995,13 @@ for (s in Background_Strains) {
     ggtitle("Raw L vs K for strains falling outside 2SD of the K mean at each conc") +
     theme_publication_legend_right()
   
-  pdf(paste(outDir_QC, "Raw_L_vs_K_for_strains_2SD_outside_mean_K.pdf", sep = ""), width = 10, height = 8)
+  pdf(file.path(outDir_QC, "Raw_L_vs_K_for_strains_2SD_outside_mean_K.pdf"), width = 10, height = 8)
   print(Outside_2SD_K_L_vs_K)
 
   dev.off()
 
   pgg <- ggplotly(Outside_2SD_K_L_vs_K)
-  plotly_path <- paste(outDir_QC, "RawL_vs_K_for_strains_outside_2SD_K.html", sep = "")
+  plotly_path <- file.path(outDir_QC, "RawL_vs_K_for_strains_outside_2SD_K.html")
   saveWidget(pgg, file = plotly_path, selfcontained = TRUE)
 
   Outside_2SD_K_delta_background_vs_K <-
@@ -1006,13 +1010,13 @@ for (s in Background_Strains) {
     ggtitle("DeltaBackground vs K for strains falling outside 2SD of the K mean at each conc") +
     theme_publication_legend_right()
 
-  pdf(paste(outDir_QC, "DeltaBackground_vs_K_for_strains_2SD_outside_mean_K.pdf", sep = ""), width = 10, height = 8)
+  pdf(file.path(outDir_QC, "DeltaBackground_vs_K_for_strains_2SD_outside_mean_K.pdf"), width = 10, height = 8)
   Outside_2SD_K_delta_background_vs_K
   dev.off()
   pgg <- ggplotly(Outside_2SD_K_delta_background_vs_K)
 
   # pgg
-  plotly_path <- paste(outDir_QC, "DeltaBackground_vs_K_for_strains_outside_2SD_K.html", sep = "")
+  plotly_path <- file.path(outDir_QC, "DeltaBackground_vs_K_for_strains_outside_2SD_K.html")
   saveWidget(pgg, file = plotly_path, selfcontained = TRUE)
 
   # Get the background strain mean values at the no drug conc to calculate shift
@@ -1046,7 +1050,7 @@ for (s in Background_Strains) {
     X2_temp <- X2[X2$Conc_Num == Concentration, ]
     if (Concentration == 0) {
       X2_new <- X2_temp
-      print(paste("Check loop order, conc =", Concentration, sep = " "))
+      sprintf("Check loop order, conc = %f", Concentration)
     }
     if (Concentration > 0) {
       try(X2_temp[X2_temp$l == 0 & !is.na(X2_temp$l), ]$l <- X_stats_BY_L_within_2SD_K$max[i])
@@ -1055,7 +1059,7 @@ for (s in Background_Strains) {
       # X2_temp[X2_temp$K == 0, ]$K <- X_stats_ALL_K$max[i]
       # X2_temp[X2_temp$r == 0, ]$r <- X_stats_ALL_r$max[i]
       # X2_temp[X2_temp$AUC == 0, ]$AUC <- X_stats_ALL_AUC$max[i]
-      print(paste("Check loop order, conc =", Concentration, sep = " "))
+      sprintf("Check loop order, conc = %f", Concentration)
       X2_new <- rbind(X2_new, X2_temp)
     }
   }
@@ -1075,13 +1079,13 @@ for (s in Background_Strains) {
     X2_RF_temp <- X2_RF[X2_RF$Conc_Num == Concentration, ]
     if (Concentration == 0) {
       X2_RF_new <- X2_RF_temp
-      print(paste("Check loop order, conc =", Concentration, sep = " "))
+      sprintf("Check loop order, conc = %f", Concentration)
     }
     if (Concentration > 0) {
       try(X2_RF_temp[X2_RF_temp$l == 0 & !is.na(X2_RF_temp$l), ]$l <- X_stats_BY_L_within_2SD_K$max[i])
       try(X2_temp[X2_temp$l >= X_stats_BY_L_within_2SD_K$max[i] & !is.na(X2_temp$l), ]$SM <- 1)
       try(X2_RF_temp[X2_RF_temp$l >= X_stats_BY_L_within_2SD_K$max[i] & !is.na(X2_RF_temp$l), ]$l <- X_stats_BY_L_within_2SD_K$max[i])
-      print(paste("If error, refs have no L values outside theoretical max L, for REFs, conc =", Concentration, sep = " "))
+      sprintf("If error, refs have no L values outside theoretical max L, for REFs, conc = %f", Concentration)
       X2_RF_new <- rbind(X2_RF_new, X2_RF_temp)
     }
   }
@@ -1446,7 +1450,7 @@ for (s in Background_Strains) {
   InteractionScores_RF$Z_lm_AUC <- (InteractionScores_RF$lm_Score_AUC - lm_mean_AUC) / (lm_sd_AUC)
   InteractionScores_RF <- InteractionScores_RF[order(InteractionScores_RF$Z_lm_L, decreasing = TRUE), ]
   InteractionScores_RF <- InteractionScores_RF[order(InteractionScores_RF$NG, decreasing = TRUE), ]
-  write.csv(InteractionScores_RF, paste(outDir, "RF_ZScores_Interaction.csv", sep = ""), row.names = FALSE)
+  write.csv(InteractionScores_RF, file.path(outDir, "RF_ZScores_Interaction.csv"), row.names = FALSE)
   
   for (i in 1:num_genes_RF) {
     Gene_Sel <- unique(InteractionScores_RF$OrfRep)[i]
@@ -1548,7 +1552,7 @@ for (s in Background_Strains) {
     }
   }
   print("Pass RF ggplot loop")
-  write.csv(X_stats_interaction_ALL_RF_final, paste(outDir, "RF_ZScore_Calculations.csv", sep = ""), row.names = FALSE)
+  write.csv(X_stats_interaction_ALL_RF_final, file.path(outDir, "RF_ZScore_Calculations.csv"), row.names = FALSE)
   
   # Part 5 - Get Zscores for Gene deletion strains
   
@@ -1904,7 +1908,7 @@ for (s in Background_Strains) {
   InteractionScores <- InteractionScores[order(InteractionScores$NG, decreasing = TRUE), ]
   df_order_by_OrfRep <- unique(InteractionScores$OrfRep)
   # X_stats_interaction_ALL <- X_stats_interaction_ALL[order(X_stats_interaction_ALL$NG, decreasing = TRUE), ]
-  write.csv(InteractionScores, paste(outDir, "ZScores_Interaction.csv", sep = ""), row.names = FALSE)
+  write.csv(InteractionScores, file.path(outDir, "ZScores_Interaction.csv"), row.names = FALSE)
   
   InteractionScores_deletion_enhancers_L <-
     InteractionScores[InteractionScores$Avg_Zscore_L >= 2, ]
@@ -1957,25 +1961,25 @@ for (s in Background_Strains) {
     InteractionScores_deletion_enhancers_Avg_Zscore_Suppressors_lm_K[
       !is.na(InteractionScores_deletion_enhancers_Avg_Zscore_Suppressors_lm_K$OrfRep), ]
   write.csv(InteractionScores_deletion_enhancers_L,
-    paste(outDir, "ZScores_Interaction_DeletionEnhancers_L.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionEnhancers_L.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_K,
-    paste(outDir, "ZScores_Interaction_DeletionEnhancers_K.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionEnhancers_K.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_suppressors_L,
-    paste(outDir, "ZScores_Interaction_DeletionSuppressors_L.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionSuppressors_L.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_suppressors_K,
-    paste(outDir, "ZScores_Interaction_DeletionSuppressors_K.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionSuppressors_K.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_and_Suppressors_L,
-    paste(outDir, "ZScores_Interaction_DeletionEnhancers_and_Suppressors_L.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionEnhancers_and_Suppressors_L.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_and_Suppressors_K,
-    paste(outDir, "ZScores_Interaction_DeletionEnhancers_and_Suppressors_K.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionEnhancers_and_Suppressors_K.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_lm_Suppressors_AvgZscore_L,
-    paste(outDir, "ZScores_Interaction_Suppressors_and_lm_Enhancers_L.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_Suppressors_and_lm_Enhancers_L.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_Avg_Zscore_Suppressors_lm_L,
-    paste(outDir, "ZScores_Interaction_Enhancers_and_lm_Suppressors_L.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_Enhancers_and_lm_Suppressors_L.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_lm_Suppressors_AvgZscore_K,
-    paste(outDir, "ZScores_Interaction_Suppressors_and_lm_Enhancers_K.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_Suppressors_and_lm_Enhancers_K.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_Avg_Zscore_Suppressors_lm_K,
-    paste(outDir, "ZScores_Interaction_Enhancers_and_lm_Suppressors_K.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_Enhancers_and_lm_Suppressors_K.csv"), row.names = FALSE)
   
   # Get enhancers and suppressors for linear regression
   InteractionScores_deletion_enhancers_L_lm <-
@@ -2010,19 +2014,19 @@ for (s in Background_Strains) {
       !is.na(InteractionScores_deletion_enhancers_and_Suppressors_K_lm$OrfRep), ]
   
   write.csv(InteractionScores_deletion_enhancers_L_lm,
-    paste(outDir, "ZScores_Interaction_DeletionEnhancers_L_lm.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionEnhancers_L_lm.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_K_lm,
-    paste(outDir, "ZScores_Interaction_DeletionEnhancers_K_lm.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionEnhancers_K_lm.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_suppressors_L_lm,
-    paste(outDir, "ZScores_Interaction_DeletionSuppressors_L_lm.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionSuppressors_L_lm.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_suppressors_K_lm,
-    paste(outDir, "ZScores_Interaction_DeletionSuppressors_K_lm.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionSuppressors_K_lm.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_and_Suppressors_L_lm,
-    paste(outDir, "ZScores_Interaction_DeletionEnhancers_and_Suppressors_L_lm.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionEnhancers_and_Suppressors_L_lm.csv"), row.names = FALSE)
   write.csv(InteractionScores_deletion_enhancers_and_Suppressors_K_lm,
-    paste(outDir, "ZScores_Interaction_DeletionEnhancers_and_Suppressors_K_lm.csv", sep = ""), row.names = FALSE)
+    file.path(outDir, "ZScores_Interaction_DeletionEnhancers_and_Suppressors_K_lm.csv"), row.names = FALSE)
-  write.csv(Labels, file = paste(studyInfo), row.names = FALSE)
+  # write.csv(Labels, studyInfo, row.names = FALSE)
-  # write.table(Labels, file = paste("../Code/StudyInfo.txt"), sep = "\t", row.names = FALSE)
+  # write.table(Labels, file.path("../Code/StudyInfo.txt"), sep = "\t", row.names = FALSE)
   
   for (i in 1:num_genes) {
     Gene_Sel <- unique(InteractionScores$OrfRep)[i]
@@ -2113,11 +2117,11 @@ for (s in Background_Strains) {
     }
   }
   print("Pass Int ggplot loop")
-  write.csv(X_stats_interaction_ALL_final, paste(outDir, "ZScore_Calculations.csv", sep = ""), row.names = FALSE)
+  write.csv(X_stats_interaction_ALL_final, file.path(outDir, "ZScore_Calculations.csv"), row.names = FALSE)
   
   Blank <- ggplot(X2_RF) + geom_blank()
   
-  pdf(paste(outDir, "InteractionPlots.pdf", sep = ""), width = 16, height = 16, onefile = TRUE)
+  pdf(file.path(outDir, "InteractionPlots.pdf"), width = 16, height = 16, onefile = TRUE)
   
   X_stats_X2_RF <- ddply(
     X2_RF,
@@ -2344,7 +2348,7 @@ for (s in Background_Strains) {
 
   dev.off()
 
-  pdf(paste(outDir, "RF_InteractionPlots.pdf", sep = ""), width = 16, height = 16, onefile = TRUE)
+  pdf(file.path(outDir, "RF_InteractionPlots.pdf"), width = 16, height = 16, onefile = TRUE)
 
   X_stats_X2_RF <- ddply(
     X2_RF,
@@ -2732,7 +2736,7 @@ for (s in Background_Strains) {
     geom_hline(yintercept = c(-3, 3)) + geom_point(size = 0.1, shape = 3) +
     theme_publication()
   
-  pdf(paste(outDir, "RankPlots.pdf", sep = ""), width = 18, height = 12, onefile = TRUE)
+  pdf(file.path(outDir, "RankPlots.pdf"), width = 18, height = 12, onefile = TRUE)
   
   grid.arrange(
     Rank_L_1SD,
@@ -2866,7 +2870,7 @@ for (s in Background_Strains) {
     geom_hline(yintercept = c(-3, 3)) + geom_point(size = 0.1, shape = 3) +
     theme_publication()
   
-  pdf(paste(outDir, "RankPlots_lm.pdf", sep = ""), width = 18, height = 12, onefile = TRUE)
+  pdf(file.path(outDir, "RankPlots_lm.pdf"), width = 18, height = 12, onefile = TRUE)
   
   grid.arrange(
     Rank_L_1SD_lm,
@@ -2916,7 +2920,7 @@ for (s in Background_Strains) {
   get_lm_AUC <- lm(X_NArm$Z_lm_AUC ~ X_NArm$Avg_Zscore_AUC)
   AUC_lm <- summary(get_lm_AUC)
   
-  pdf(paste(outDir, "Avg_Zscore_vs_lm_NA_rm.pdf", sep = ""), width = 16, height = 12, onefile = TRUE)
+  pdf(file.path(outDir, "Avg_Zscore_vs_lm_NA_rm.pdf"), width = 16, height = 12, onefile = TRUE)
   
   print(ggplot(X_NArm, aes(Avg_Zscore_L, Z_lm_L)) +
     geom_point(aes(color = Overlap), shape = 3) +
@@ -2955,7 +2959,7 @@ for (s in Background_Strains) {
     annotate("text", x = 0, y = 0, label = paste("R-squared = ", round(L_lm$r.squared, 2))) + theme_publication_legend_right()
   
   pgg <- ggplotly(lm_v_Zscore_L)
-  plotly_path <- paste(outDir, "Avg_Zscore_vs_lm_NA_rm.html", sep = "")
+  plotly_path <- file.path(outDir, "Avg_Zscore_vs_lm_NA_rm.html")
   saveWidget(pgg, file = plotly_path, selfcontained = TRUE)
   
   X_NArm$L_Rank <- rank(X_NArm$Avg_Zscore_L)
@@ -2978,7 +2982,7 @@ for (s in Background_Strains) {
   AUC_lm2 <- summary(get_lm_AUC2)
   num_genes_NArm2 <- (dim(X_NArm)[1]) / 2
   
-  pdf(paste(outDir, "Avg_Zscore_vs_lm_ranked_NA_rm.pdf", sep = ""), width = 16, height = 12, onefile = TRUE)
+  pdf(file.path(outDir, "Avg_Zscore_vs_lm_ranked_NA_rm.pdf"), width = 16, height = 12, onefile = TRUE)
   
   print(
     ggplot(X_NArm, aes(L_Rank, L_Rank_lm)) +
@@ -3114,7 +3118,7 @@ for (s in Background_Strains) {
     geom_hline(yintercept = c(-3, 3)) + geom_point(size = 0.1, shape = 3) +
     theme_publication()
   
-  pdf(paste(outDir, "RankPlots_naRM.pdf", sep = ""), width = 18, height = 12, onefile = TRUE)
+  pdf(file.path(outDir, "RankPlots_naRM.pdf"), width = 18, height = 12, onefile = TRUE)
   
   grid.arrange(
     Rank_L_1SD,
@@ -3234,7 +3238,7 @@ for (s in Background_Strains) {
     geom_hline(yintercept = c(-3, 3)) + geom_point(size = 0.1, shape = 3) +
     theme_publication()
   
-  pdf(paste(outDir, "RankPlots_lm_naRM.pdf", sep = ""), width = 18, height = 12, onefile = TRUE)
+  pdf(file.path(outDir, "RankPlots_lm_naRM.pdf"), width = 18, height = 12, onefile = TRUE)
   
   grid.arrange(
     Rank_L_1SD_lm,
@@ -3273,7 +3277,7 @@ L_lm_5 <- summary(get_lm_5)
 get_lm_6 <- lm(X_NArm$Z_lm_AUC ~ X_NArm$Z_lm_r)
 L_lm_6 <- summary(get_lm_6)
 
-pdf(file = paste(outDir, "Correlation_CPPs.pdf", sep = ""), width = 10, height = 7, onefile = TRUE)
+pdf(file.path(outDir, "Correlation_CPPs.pdf"), width = 10, height = 7, onefile = TRUE)
 
 ggplot(X_NArm, aes(Z_lm_L, Z_lm_K)) +
   geom_point(shape = 3, color = "gray70") +
@@ -3482,5 +3486,5 @@ ggplot(X_NArm, aes(Z_lm_r, Z_lm_AUC)) +
 
 dev.off()
 
-# write.csv(Labels, file = paste("../Code/Parameters.csv"), row.names = FALSE)
+# write.csv(Labels, file.path("../Code/Parameters.csv"), row.names = FALSE)
 timestamp()

workflow/qhtcp-workflow

@@ -14,7 +14,7 @@
 # Insert a general description of Q-HTCP and the Q-HTCP process here.
 
 shopt -s extglob # Turn on extended globbing
-DEBUG=1 # Turn debugging ON by default during development
+DEBUG=${DEBUG:-1} # Turn debugging ON by default during development
 
 # @description Use `--help` to print the help message.
 # @internal
@@ -25,13 +25,13 @@ print_help() {
 
   cat <<-EOF
 		USAGE:
-		  script-run-workflow [[OPTION] [VALUE]]...
+		  qhtcp-workflow [[OPTION] [VALUE]]...
 
 		  Some options (--project, --include, --exclude) can be passed multiple times or
 		  by using comma-separated strings (see EXAMPLES below)
 
 		OPTIONS:
-		  --project, -p PROJECT
+		  --project, -p PROJECT[,PROJECT...]
 		    PROJECT should follow the pattern ${PROJECT_PREFIX}_PROJECT_NAME
 		  --module, -m MODULE[,MODULE...]
 		    See MODULES section below for list of available modules
@@ -65,13 +65,13 @@ print_help() {
 		  BiocManager: ${depends_bioc[@]}
 
 		EXAMPLES:
-		  script-run-workflow --module ${ALL_MODULES[0]} --module ${ALL_MODULES[1]}
+		  qhtcp-workflow --module ${ALL_MODULES[0]} --module ${ALL_MODULES[1]}
-		  script-run-workflow --project ${PROJECT_PREFIX}_MY_PROJECT --module ${ALL_MODULES[0]} --module ${ALL_MODULES[1]}
+		  qhtcp-workflow --project ${PROJECT_PREFIX}_MY_PROJECT --module ${ALL_MODULES[0]} --module ${ALL_MODULES[1]}
-		  script-run-workflow --project ${PROJECT_PREFIX}_MY_PROJECT --module ${ALL_MODULES[1]} --module ${ALL_MODULES[2]} --yes
+		  qhtcp-workflow --project ${PROJECT_PREFIX}_MY_PROJECT --module ${ALL_MODULES[1]} --module ${ALL_MODULES[2]} --yes
-		  script-run-workflow --module=${ALL_MODULES[0]},${ALL_MODULES[1]}
+		  qhtcp-workflow --module=${ALL_MODULES[0]},${ALL_MODULES[1]}
-		  script-run-workflow --project=${PROJECT_PREFIX}_MY_PROJECT,${PROJECT_PREFIX}_MY_OTHER_PROJECT
+		  qhtcp-workflow --project=${PROJECT_PREFIX}_MY_PROJECT,${PROJECT_PREFIX}_MY_OTHER_PROJECT
-		  script-run-workflow --project=${PROJECT_PREFIX}_MY_PROJECT,${PROJECT_PREFIX}_MY_OTHER_PROJECT --module=${ALL_MODULES[1]},${ALL_MODULES[2]} --yes --debug
+		  qhtcp-workflow --project=${PROJECT_PREFIX}_MY_PROJECT,${PROJECT_PREFIX}_MY_OTHER_PROJECT --module=${ALL_MODULES[1]},${ALL_MODULES[2]} --yes --debug
-		  script-run-workflow --project=${PROJECT_PREFIX}_MY_PROJECT --wrapper ${ALL_WRAPPERS[2]} \"/path/to/genefile.txt,/path/to/output/dir\" --wrapper ${ALL_WRAPPERS[3]} \"/path/to/sgofile\"
+		  qhtcp-workflow --project=${PROJECT_PREFIX}_MY_PROJECT --wrapper ${ALL_WRAPPERS[2]} \"/path/to/genefile.txt,/path/to/output/dir\" --wrapper ${ALL_WRAPPERS[3]} \"/path/to/sgofile\"
 	EOF
 }
 
@@ -506,6 +506,7 @@ interactive_header() {
       printf "%d. %s\n" $((i+1)) "${ALL_WRAPPERS[i]}"
     done
   fi
+  echo ""
 
   # Let user choose or add project(s)
   if [[ ${#PROJECTS[@]} -eq 0 ]]; then
@@ -630,7 +631,7 @@ module install_dependencies
 #
 # #### Perl
 #
-# * `cpan File::Map ExtUtils::PkgConfig GD GO::TermFinder`
+# * `cpan -I -i File::Map ExtUtils::PkgConfig GD GO::TermFinder`
 #
 # #### R
 #
@@ -643,10 +644,14 @@ install_dependencies() {
   debug "Running: ${FUNCNAME[0]} $*"
 
   # Dependency arrays
-  depends_rpm=(graphviz pandoc pdftk-java gd-devel perl-CPAN shdoc nano rsync coreutils libcurl-devel openssl-devel harfbuzz-devel fribidi-devel R-core R-core-devel)
+  depends_rpm=(graphviz pandoc pdftk-java gd-devel perl-CPAN shdoc nano
-  depends_deb=(graphviz pandoc pdftk-java libgd-dev perl shdoc nano rsync coreutils libcurl-dev openssl-dev libharfbuzz-dev libfribidi-dev r-base r-base-dev)
+   rsync coreutils libcurl-devel openssl-devel harfbuzz-devel fribidi-devel
+   R-core R-core-devel)
+  depends_deb=(graphviz pandoc pdftk-java libgd-dev perl shdoc nano rsync
+    coreutils libcurl-dev openssl-dev libharfbuzz-dev libfribidi-dev r-base r-base-dev)
   depends_brew=(graphiz pandoc gd pdftk-java shdoc nano perl rsync coreutils harfbuzz fribidi r)
-  depends_perl=(Test::Warnings Test::Fatal File::Map Sub::Uplevel ExtUtils::Config ExtUtils::PkgConfig IPC::Run Module::Build::Tiny IPC::Run GD GO::TermFinder)
+  depends_perl=(Test::Warnings Test::Fatal File::Map Sub::Uplevel ExtUtils::Config
+    ExtUtils::PkgConfig IPC::Run Module::Build::Tiny GD GO::TermFinder)
   depends_r=(BiocManager ontologyIndex ggrepel tidyverse sos openxlsx ggplot2 
     plyr extrafont gridExtra gplots stringr plotly ggthemes pandoc rmarkdown
     plotly htmlwidgets gplots gdata)
@@ -1791,6 +1796,8 @@ wrapper r_interactions
 # * Replace 1:length() with seq_along()
 # * Re-enable disabled linter checks
 # * Reduce cyclomatic complexity of some of the for loops
+# * There needs to be one point of truth for the SD factor
+# * Replace most paste() functions with printf()
 #
 # NOTES
 #
@@ -1930,6 +1937,12 @@ r_add_shift_values() {
 
 wrapper r_create_heat_maps
 # @description Execute createHeatMaps.R
+#
+# TODO
+# * Needs more looping for brevity
+#
+#
+#
 # @arg $1 string The final shift table (REMcWithShift.csv)
 # @arg $2 string The output directory
 r_create_heat_maps() {
@@ -2151,7 +2164,7 @@ generate_markdown() {
 }
 
 
-# @description The main loop of script-run-workflow
+# @description The main loop of qhtcp-workflow
 # May eventually need to add git ops
 # Passes on arguments
 # Most variables in main() are user configurable or can be overriden by env