diff mda_heatmap_gen/CHM.R @ 0:73aa1f80c237 draft

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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/mda_heatmap_gen/CHM.R	Thu Apr 07 10:54:23 2016 -0400
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+### 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
+
+performDataOrdering<-function(dataFile, rowOrderMethod, rowDistanceMeasure, rowAgglomerationMethod, colOrderMethod, colDistanceMeasure, colAgglomerationMethod,rowOrderFile, colOrderFile, rowDendroFile, colDendroFile)
+{ 
+   dataMatrix = read.table(dataFile, header=TRUE, sep = "\t", row.names = 1, as.is=TRUE)
+   rowOrder <-  createOrdering(dataMatrix, rowOrderMethod, "row", rowDistanceMeasure, rowAgglomerationMethod)  
+   if (rowOrderMethod == "Hierarchical") {
+      writeHCDataTSVs(rowOrder, rowDendroFile, rowOrderFile)
+   } else {
+      writeOrderTSV(rowOrder, rownames(dataMatrix), rowOrderFile)
+   }
+
+   colOrder <-  createOrdering(dataMatrix, colOrderMethod, "col", colDistanceMeasure, colAgglomerationMethod)  
+   if (colOrderMethod == "Hierarchical") {
+      writeHCDataTSVs(colOrder, colDendroFile, colOrderFile)
+   } 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)
+}
+
+
+
+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])
+
+#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]))