--- a/CHM.R	Thu Jan 26 10:18:00 2017 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,146 +0,0 @@
-### This method generates a row and column ordering given an input matrix and ordering methods.
-###
-### matrixData - numeric matrix 
-### rowOrderMethod - Hierarchical, Original, Random
-### rowDistanceMeasure - For clustering, distance measure. May be: euclidean, binary, manhattan, maximum, canberra, minkowski, or correlation.
-### rowAgglomerationMethod - For clustering, agglomeration method.  May be:  'average' for Average Linkage, 'complete' for Complete Linkage,
-###                                                                          'single' for Single Linkage, 'ward', 'mcquitty', 'median', or 'centroid'.
-### colOrderMethod 
-### colDistanceMeasure
-### colAgglomerationMethod
-### rowOrderFile - output file of order of rows 
-### rowDendroFile - output file of row dendrogram  
-### colOrderFile - output file of order of cols
-### colDendroFile - output file of col dendrogram
-### rowCut - For rows the number of classifications to automatically generate based on dendrogram into a classification file.  0 for turned off.
-### colCut - For columns the number of classifications to automatically generate based on dendrogram into a classification file.  0 for turned off.
-
-performDataOrdering<-function(dataFile, rowOrderMethod, rowDistanceMeasure, rowAgglomerationMethod, colOrderMethod, colDistanceMeasure, colAgglomerationMethod,rowOrderFile, colOrderFile, rowDendroFile, colDendroFile, rowCut, colCut)
-{ 
-   dataMatrix = read.table(dataFile, header=TRUE, sep = "\t", row.names = 1, as.is=TRUE, na.strings=c("NA","N/A","-","?"))
-   rowOrder <-  createOrdering(dataMatrix, rowOrderMethod, "row", rowDistanceMeasure, rowAgglomerationMethod)  
-   if (rowOrderMethod == "Hierarchical") {
-      writeHCDataTSVs(rowOrder, rowDendroFile, rowOrderFile)
-      writeHCCut(rowOrder, rowCut, paste(rowOrderFile,".cut", sep=""))
-   } else {
-      writeOrderTSV(rowOrder, rownames(dataMatrix), rowOrderFile)
-   }
-
-   colOrder <-  createOrdering(dataMatrix, colOrderMethod, "col", colDistanceMeasure, colAgglomerationMethod)  
-   if (colOrderMethod == "Hierarchical") {
-      writeHCDataTSVs(colOrder, colDendroFile, colOrderFile)
-      writeHCCut(colOrder, colCut, paste(colOrderFile,".cut", sep=""))
-   } else {
-      writeOrderTSV(colOrder, colnames(dataMatrix), colOrderFile)
-   }
-}
-
-#creates output files for hclust ordering
-writeHCDataTSVs<-function(uDend, outputHCDataFileName, outputHCOrderFileName)
-{
-   data<-cbind(uDend$merge, uDend$height, deparse.level=0)
-   colnames(data)<-c("A", "B", "Height")
-   write.table(data, file = outputHCDataFileName, append = FALSE, quote = FALSE, sep = "\t", row.names=FALSE)
- 
-   data=matrix(,length(uDend$labels),2);
-   for (i in 1:length(uDend$labels)) {
-      data[i,1] = uDend$labels[i];
-      data[i,2] = which(uDend$order==i);
-   }
-   colnames(data)<-c("Id", "Order")
-   write.table(data, file = outputHCOrderFileName, append = FALSE, quote = FALSE, sep = "\t", row.names=FALSE)
-}
-
-#creates order file for non-clustering methods
-writeOrderTSV<-function(newOrder, originalOrder, outputHCOrderFileName)
-{
-   data=matrix(,length(originalOrder),2);
-   for (i in 1:length(originalOrder)) {
-      data[i,1] = originalOrder[i];
-      data[i,2] = which(newOrder==originalOrder[i]);
-   }
-   colnames(data)<-c("Id", "Order")
-   write.table(data, file = outputHCOrderFileName, append = FALSE, quote = FALSE, sep = "\t", row.names=FALSE)
-}
-
-#creates a classification file based on user specified cut of dendrogram
-writeHCCut<-function(uDend, cutNum, outputCutFileName)
-{
-   if (cutNum < 2) {
-      return()
-   }
-   print (paste("Writing cut file ", outputCutFileName))
-   cut <- cutree(uDend, cutNum);
-   id <- names(cut);
-   data=matrix(,length(cut),2);
-   for (i in 1:length(cut)) {
-      data[i,1] = id[i];
-      data[i,2] = sprintf("Cluster %d", cut[i]);
-   }
-
-   write.table(data, file = outputCutFileName, append = FALSE, quote = FALSE, sep = "\t", row.names=FALSE, col.names = FALSE);
-}
-
-
-createOrdering<-function(matrixData, orderMethod, direction, distanceMeasure, agglomerationMethod)
-{
-  ordering <- NULL
-
-  if (orderMethod == "Hierarchical")
-  {
-
-    # Compute dendrogram for "Distance Metric"
-    distVals <- NULL
-    if(direction=="row") {
-      if (distanceMeasure == "correlation") {
-        geneGeneCor <- cor(t(matrixData), use="pairwise")
-        distVals <- as.dist((1-geneGeneCor)/2)
-      } else {
-        distVals <- dist(matrixData, method=distanceMeasure)
-      }
-    } else { #column
-      if (distanceMeasure == "correlation") {
-        geneGeneCor <- cor(matrixData, use="pairwise")
-        distVals <- as.dist((1-geneGeneCor)/2)
-      } else {
-        distVals <- dist(t(matrixData), method=distanceMeasure)
-      }
-    }
-
-#    if (agglomerationMethod == "ward") {
-#      ordering <- hclust(distVals * distVals, method="ward.D2")
-#    } else {
-      ordering <- hclust(distVals, method=agglomerationMethod)
-#    }
-  }
-  else if (orderMethod == "Random")
-  {
-    if(direction=="row") {
-       headerList <- rownames(matrixData)
-       ordering <- sample(headerList, length(headerList)) 
-    } else {
-       headerList <- colnames(matrixData)
-       ordering <- sample(headerList, length(headerList)) 
-    }
-  }
-  else if (orderMethod == "Original")
-  {
-    if(direction=="row") {
-       ordering <- rownames(matrixData) 
-    } else {
-       ordering <- colnames(matrixData) 
-    }
-  } else {
-    stop("createOrdering -- failed to find ordering method")
-  }
-  return(ordering)
-}
-### Initialize command line arguments and call performDataOrdering
-
-options(warn=-1)
-
-args = commandArgs(TRUE)
-
-performDataOrdering(dataFile=args[1], rowOrderMethod=args[2], rowDistanceMeasure=args[3], rowAgglomerationMethod=args[4], colOrderMethod=args[5], colDistanceMeasure=args[6], colAgglomerationMethod=args[7],rowOrderFile=args[8], colOrderFile=args[9], rowDendroFile=args[10], colDendroFile=args[11], rowCut=args[12], colCut=args[13])
-
-#suppressWarnings(performDataOrdering(dataFile=args[1], rowOrderMethod=args[2], rowDistanceMeasure=args[3], rowAgglomerationMethod=args[4], colOrderMethod=args[5], colDistanceMeasure=args[6], colAgglomerationMethod=args[7],rowOrderFile=args[8], colOrderFile=args[9], rowDendroFile=args[10], colDendroFile=args[11]))

Binary file GalaxyMapGen.jar has changed

--- a/heatmap.sh	Thu Jan 26 10:18:00 2017 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,47 +0,0 @@
-echo $1 $2 $3 $4 $5 $6 $7 $8 $9 ${10} ${11} ${12} ${13} ${14} ${15} ${16} ${17}
-#create temp directory for row and col order and dendro files.
-tdir=${11}/$(date +%y%m%d%M%S)
-echo $tdir
-mkdir $tdir
-#run R to cluster matrix
-output="$(R --slave --vanilla --file=${11}/CHM.R --args $3 $4 $5 $6 $7 $8 $9 $tdir/ROfile.txt $tdir/COfile.txt $tdir/RDfile.txt $tdir/CDfile.txt ${12} ${13} ${14} ${15} 2>&1)"
-rc=$?;
-if [ $rc != 0 ]
-then
-  echo $output;
-  if [ `echo "$output" | grep -c "Inf in foreign function call"` -gt 0 ]
-  then
-    echo "";
-    echo "Note: This error can occur when there is no variation in a row or column.  Try a different distance measure or remove rows/columns without variation.";
-  fi
-  exit $rc;
-fi
-
-#there are a variable number of triplicate parameters for classification bars
-count=0
-classifications=''
-
-#if row cut was done, add that autogenerated classification
-if [ ${12} -gt 1 ]
-then
-  classifications="Class $tdir/ROfile.txt.cut row_categorical"
-fi
-
-#if col cut was done, add that autogenerated classification
-if [ ${13} -gt 1 ]
-then
-  classifications="$classifications Class $tdir/COfile.txt.cut col_categorical"
-fi
-
-#now add the user provided classification files 
-for i in "$@"; do
-  if [ $count -gt 14 ]
-  then
-    classifications=$classifications' '$i
-  fi
-  count=$((count+1))
-done
-#call java program to generate NGCHM viewer files.
-java -jar ${11}/GalaxyMapGen.jar "${1}" "${2}" DataLayer1 $3 linear ${14} ${15} $4 $5 $6 $tdir/ROfile.txt $tdir/RDfile.txt $7 $8 $9 $tdir/COfile.txt $tdir/CDfile.txt ${10} $classifications
-#clean up tempdir
-rm -rf $tdir