Mercurial > repos > md-anderson-bioinformatics > heat_map_creation

comparison CHM.R @ 3:603d5c39e8dc draft

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author insilico-bob
date Thu, 26 Jan 2017 09:53:30 -0500
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2:e2b3920e20c1 3:603d5c39e8dc
1 ### This method generates a row and column ordering given an input matrix and ordering methods.
2 ###
3 ### matrixData - numeric matrix
4 ### rowOrderMethod - Hierarchical, Original, Random
5 ### rowDistanceMeasure - For clustering, distance measure. May be: euclidean, binary, manhattan, maximum, canberra, minkowski, or correlation.
6 ### rowAgglomerationMethod - For clustering, agglomeration method. May be: 'average' for Average Linkage, 'complete' for Complete Linkage,
7 ### 'single' for Single Linkage, 'ward', 'mcquitty', 'median', or 'centroid'.
8 ### colOrderMethod
9 ### colDistanceMeasure
10 ### colAgglomerationMethod
11 ### rowOrderFile - output file of order of rows
12 ### rowDendroFile - output file of row dendrogram
13 ### colOrderFile - output file of order of cols
14 ### colDendroFile - output file of col dendrogram
15 ### rowCut - For rows the number of classifications to automatically generate based on dendrogram into a classification file. 0 for turned off.
16 ### colCut - For columns the number of classifications to automatically generate based on dendrogram into a classification file. 0 for turned off.
17
18 performDataOrdering<-function(dataFile, rowOrderMethod, rowDistanceMeasure, rowAgglomerationMethod, colOrderMethod, colDistanceMeasure, colAgglomerationMethod,rowOrderFile, colOrderFile, rowDendroFile, colDendroFile, rowCut, colCut)
19 {
20 dataMatrix = read.table(dataFile, header=TRUE, sep = "\t", row.names = 1, as.is=TRUE, na.strings=c("NA","N/A","-","?"))
21 rowOrder <- createOrdering(dataMatrix, rowOrderMethod, "row", rowDistanceMeasure, rowAgglomerationMethod)
22 if (rowOrderMethod == "Hierarchical") {
23 writeHCDataTSVs(rowOrder, rowDendroFile, rowOrderFile)
24 writeHCCut(rowOrder, rowCut, paste(rowOrderFile,".cut", sep=""))
25 } else {
26 writeOrderTSV(rowOrder, rownames(dataMatrix), rowOrderFile)
27 }
28
29 colOrder <- createOrdering(dataMatrix, colOrderMethod, "col", colDistanceMeasure, colAgglomerationMethod)
30 if (colOrderMethod == "Hierarchical") {
31 writeHCDataTSVs(colOrder, colDendroFile, colOrderFile)
32 writeHCCut(colOrder, colCut, paste(colOrderFile,".cut", sep=""))
33 } else {
34 writeOrderTSV(colOrder, colnames(dataMatrix), colOrderFile)
35 }
36 }
37
38 #creates output files for hclust ordering
39 writeHCDataTSVs<-function(uDend, outputHCDataFileName, outputHCOrderFileName)
40 {
41 data<-cbind(uDend$merge, uDend$height, deparse.level=0)
42 colnames(data)<-c("A", "B", "Height")
43 write.table(data, file = outputHCDataFileName, append = FALSE, quote = FALSE, sep = "\t", row.names=FALSE)
44
45 data=matrix(,length(uDend$labels),2);
46 for (i in 1:length(uDend$labels)) {
47 data[i,1] = uDend$labels[i];
48 data[i,2] = which(uDend$order==i);
49 }
50 colnames(data)<-c("Id", "Order")
51 write.table(data, file = outputHCOrderFileName, append = FALSE, quote = FALSE, sep = "\t", row.names=FALSE)
52 }
53
54 #creates order file for non-clustering methods
55 writeOrderTSV<-function(newOrder, originalOrder, outputHCOrderFileName)
56 {
57 data=matrix(,length(originalOrder),2);
58 for (i in 1:length(originalOrder)) {
59 data[i,1] = originalOrder[i];
60 data[i,2] = which(newOrder==originalOrder[i]);
61 }
62 colnames(data)<-c("Id", "Order")
63 write.table(data, file = outputHCOrderFileName, append = FALSE, quote = FALSE, sep = "\t", row.names=FALSE)
64 }
65
66 #creates a classification file based on user specified cut of dendrogram
67 writeHCCut<-function(uDend, cutNum, outputCutFileName)
68 {
69 if (cutNum < 2) {
70 return()
71 }
72 print (paste("Writing cut file ", outputCutFileName))
73 cut <- cutree(uDend, cutNum);
74 id <- names(cut);
75 data=matrix(,length(cut),2);
76 for (i in 1:length(cut)) {
77 data[i,1] = id[i];
78 data[i,2] = sprintf("Cluster %d", cut[i]);
79 }
80
81 write.table(data, file = outputCutFileName, append = FALSE, quote = FALSE, sep = "\t", row.names=FALSE, col.names = FALSE);
82 }
83
84
85 createOrdering<-function(matrixData, orderMethod, direction, distanceMeasure, agglomerationMethod)
86 {
87 ordering <- NULL
88
89 if (orderMethod == "Hierarchical")
90 {
91
92 # Compute dendrogram for "Distance Metric"
93 distVals <- NULL
94 if(direction=="row") {
95 if (distanceMeasure == "correlation") {
96 geneGeneCor <- cor(t(matrixData), use="pairwise")
97 distVals <- as.dist((1-geneGeneCor)/2)
98 } else {
99 distVals <- dist(matrixData, method=distanceMeasure)
100 }
101 } else { #column
102 if (distanceMeasure == "correlation") {
103 geneGeneCor <- cor(matrixData, use="pairwise")
104 distVals <- as.dist((1-geneGeneCor)/2)
105 } else {
106 distVals <- dist(t(matrixData), method=distanceMeasure)
107 }
108 }
109
110 # if (agglomerationMethod == "ward") {
111 # ordering <- hclust(distVals * distVals, method="ward.D2")
112 # } else {
113 ordering <- hclust(distVals, method=agglomerationMethod)
114 # }
115 }
116 else if (orderMethod == "Random")
117 {
118 if(direction=="row") {
119 headerList <- rownames(matrixData)
120 ordering <- sample(headerList, length(headerList))
121 } else {
122 headerList <- colnames(matrixData)
123 ordering <- sample(headerList, length(headerList))
124 }
125 }
126 else if (orderMethod == "Original")
127 {
128 if(direction=="row") {
129 ordering <- rownames(matrixData)
130 } else {
131 ordering <- colnames(matrixData)
132 }
133 } else {
134 stop("createOrdering -- failed to find ordering method")
135 }
136 return(ordering)
137 }
138 ### Initialize command line arguments and call performDataOrdering
139
140 options(warn=-1)
141
142 args = commandArgs(TRUE)
143
144 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])
145
146 #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]))