# HG changeset patch
# User insilico-bob
# Date 1500579066 14400
# Node ID 16593e40c2cd1aead80dbcfdc157b73dda03cab9
# Parent  e01b833f5d4382bbd420d8341f0b5a2ac2bfc738
Version 2.0.5

diff -r e01b833f5d43 -r 16593e40c2cd CHM.R
--- a/CHM.R	Fri Feb 03 13:20:50 2017 -0500
+++ b/CHM.R	Thu Jul 20 15:31:06 2017 -0400
@@ -21,17 +21,12 @@
    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)
    }
 }
 
@@ -51,18 +46,6 @@
    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)
 {
diff -r e01b833f5d43 -r 16593e40c2cd GalaxyMapGen.jar
Binary file GalaxyMapGen.jar has changed
diff -r e01b833f5d43 -r 16593e40c2cd heatmap.sh
--- a/heatmap.sh	Fri Feb 03 13:20:50 2017 -0500
+++ b/heatmap.sh	Thu Jul 20 15:31:06 2017 -0400
@@ -1,8 +1,21 @@
 echo $1 $2 $3 $4 $5 $6 $7 $8 $9 ${10} ${11} ${12} ${13} ${14} ${15} ${16} ${17}
+
+#run python to validate the input matrix and covariate files (if any)
+#output="$(python  ${11}/mda_heatmap_gen.py $@)"
+output=$(python  ${11}/mda_heatmap_gen.py "$@")
+rc=$?;
+echo $output;
+if [ $rc != 0 ]
+then
+  exit $rc;
+fi
+
+
 #create temp directory for row and col order and dendro files.
 tdir=${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} ${15} 2>&1)"
 rc=$?;
diff -r e01b833f5d43 -r 16593e40c2cd mda_heatmap_gen.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/mda_heatmap_gen.py	Thu Jul 20 15:31:06 2017 -0400
@@ -0,0 +1,250 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# python shell program to validate ng-chm heat map input matrix file and covariate file formats before calling java shell -- bob brown
+
+import subprocess           #you must import subprocess so that python can talk to the command line
+import sys
+import os
+import re
+#import config
+import traceback
+#import commons
+
+#ConfigVals = config.Config("../rppaConf.txt")
+
+def main():
+    
+    try:
+        print '\nStarting Heat Map file validation ......' 
+        #print "\nheat map sys args len and values = ",len(sys.argv), str(sys.argv)   #, '++',argvals
+
+      
+        error= False
+        endCovarParam=  len(sys.argv)-2 # IF any ending of loc for covar triplet info 
+        startCovarParam=    17 # beginning loc for covar triplet info
+        inMatrix=           sys.argv[3]
+
+        for i in range( endCovarParam, 15, -3):
+            if len(sys.argv[i]) > 6:
+                if sys.argv[i][0:4].find('row_') == 0 or sys.argv[i][0:7].find('column_') == 0:  # 0 is match start position
+                    startCovarParam= i-2                
+                    #print "\nHeat map arg 3 and start covariate index on = " ,str(sys.argv[3]),' - ', startCovarParam, ' covar name= ',str(sys.argv[startCovarParam:])
+                #else: print '\nCovariate param row or column not found at i', i, str(sys.argv[i])
+
+    #test        inMatrix= "/Users/bobbrown/Desktop/NGCHM-Galaxy-Test-Files/400x400firstRowShift.txt"
+    #test        covarFN= '/Users/bobbrown/Desktop/400x400-column-covariate-continuous-TestingErrors.txt'
+    #test        row_col_cat_contin= 'column_continuous'
+    #test        row_col_cat_contin= 'column_categorical'  
+    #test        covarLabel = 'bob test'
+    #test        numCovariates= 1
+        
+        errorInMatrix,inMatrixRowLabels,inMatrixColLabels= ValidateHMInputMatrix(inMatrix)   # verify input matrix
+        
+        print "\nFirst & last Row labels ", inMatrixRowLabels[0],inMatrixRowLabels[-1]," and Columns ", inMatrixColLabels[0],inMatrixColLabels[-1], " number Rows= ",len(inMatrixRowLabels)," number Columns= ",len(inMatrixColLabels)
+            
+    # continue reviewing covariates to catch any errors in any of the input info
+        if len(inMatrixRowLabels) < 5 or len(inMatrixColLabels) < 5: 
+            errorInMatrix = True
+            print '\n----ERROR Input matrix has too few columns and rows need to ignore validating covariate files for now'
+            
+        elif not errorInMatrix: 
+            print "\n++++ SUCCESS the Input Matrix looks good\n\n"
+            
+            i= startCovarParam
+            while i < (len(sys.argv)-2):  # todo verify this works with advances tool is one other 0->n param after this
+                covarLabel=         sys.argv[i]
+                covarLabel=         covarLabel.replace(' ','')
+                covarFN=            sys.argv[i+1]
+                covarFN=            covarFN.replace(' ','')
+                row_col_cat_contin=  sys.argv[i+2]
+                row_col_cat_contin=  row_col_cat_contin.replace(' ','')
+                i +=3
+                                             
+                print "\nSTART Validating covariate file with label= ", covarLabel, " and type= ",row_col_cat_contin
+        
+                error= ValidateHMCorvarFile(covarLabel, covarFN, row_col_cat_contin,inMatrixRowLabels,inMatrixColLabels)  # check covariate files
+    
+            if error or errorInMatrix:
+                print"\n---ERROR issues found in input or covariate files\n "
+                sys.stderr.write( "\nERROR issues found in input or covariate files see errors in Standard Output\n\n ") 
+                sys.exit(3)
+            
+                
+        print"\n FINISHED -- Validation of the Input Matrix and Covariate files (if any)\n\n"
+        
+        #print" next running the clustered heat map generator \n",str(sys.argv[11])+"/heatmap.sh "+ str(sys.argv[1:])
+    #            p = subprocess.Popen([str(sys.argv[1])+"/heatmap.sh "+ argvals], shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+            #p = subprocess.Popen([str(sys.argv[11])+"/heatmap.sh "+ str(sys.argv[1:])], shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+     
+            #retval = p.wait()  
+            #print ' Cluster and Viewer returned\n'
+            #for line in p.stdout.readlines():
+            #    print line
+                     
+#         else: 
+#             sys.stderr.write("\nERROR -- The Heat Map Generator encountered the above errors with the input file(s)\n\n")
+#             sys.exit(3) # this will error it out :)
+#     except:
+#         sys.stderr.write(str(traceback.format_exc()))
+#         sys.exit(3) # this will error it out :)
+    except Exception, err:
+        sys.stderr.write('ERROR: %sn' % str(err))
+
+    return 
+
+#+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-
+
+def ValidateHMInputMatrix(inputMatrixPath):           # This sub routine ensures that the slide design input by the user matches a slide design on record
+
+     try:
+        error= True
+    
+        inputMatrixPath= inputMatrixPath.replace(' ','')
+
+        inMatrixFH= open( inputMatrixPath, 'rU')
+        
+        #print "\nInput matrix path and name ", inputMatrixPath,"\n"
+        error= False
+
+        countRow=   0
+        lenRow1=    0
+        lenAllRows= 0
+        inMatrixRowLabels= []
+        inMatrixColLabels= []
+        
+        for rawRow in inMatrixFH:
+            countRow +=1
+            
+            rawRow= rawRow.replace('\n','')
+            eachRow=  rawRow.split('\t')
+            if countRow < 2: print 'Input Matrix start 1 to 10= ',eachRow[:10], '\n'
+            
+            if countRow == 1: 
+                lenRow1= len(eachRow)
+                inMatrixColLabels= eachRow
+                for j in range(1,lenRow1):
+                    tmp= re.search('[abcdefghijklmnopqrstuvwxyz]',eachRow[j].lower())
+                    try:
+                        if tmp.group(0) == '':  # if doesn't exist then error
+                            tmp= tmp
+                    except Exception as e:
+                        print("\n--+-+- ERROR Column Headers at position "+str(j+1)+" value appears to be non-alphanumeric --"+str(eachRow[j])+"--")
+                        sys.stderr.write("\n--+-+- ERROR Column Headers at position "+str(j+1)+" value appears to be non-alphanumeric --"+str(eachRow[j])+"--")
+                        error= True
+
+                if lenRow1 < 3:  # likely is covariate file not input matrix
+                    print"----WARNING Input  number of columns= " , str(lenRow1)," is too few likely input matrix is really a covariate file"
+                    SystemError ("----WARNING Input  number of columns= " + str(lenRow1)+" is too few likely input matrix is really a covariate file")
+                    #error= True
+                    #sys.err= 2
+            elif countRow == 2: 
+                lenAllRows= len(eachRow)
+                if (lenAllRows == lenRow1) or (lenAllRows == lenRow1+1):  #or (lenAllRows- lenRow1 == 0 or 1): 
+                    print"Validating Input matrix,  number of Labeled Columns = ", str(lenAllRows)
+                    inMatrixRowLabels.append(eachRow[0])
+
+#  allow other error to occur first
+#                     tmp= re.search('[abcdefghijklmnopqrstuvwxyz]',eachRow[0].lower())
+#                     try:
+#                         if tmp.group(0) == '':  # if doesn't exist then error
+#                             tmp= tmp
+#                     except Exception as e:
+#                         print("\n--+-+- WARNING Row Label at row 2 value appears to be non-alphanumeric --"+str(eachRow[j])+"--")
+#                         sys.stderr.write("\n--+-+- WARNING Row Label at row 2 value appears to be non-alphanumeric --"+str(eachRow[j])+"--")
+#                         #error= True
+                    if (lenAllRows == lenRow1) and (inMatrixColLabels[0]==''): inMatrixColLabels.pop(0)  #remove blank first cell
+
+                else: 
+                    print( "\n--ERROR  Input matrix number columns= "+str(lenRow1)+" in first row and the second row= "+str(lenAllRows)+" mismatch ")
+                    sys.stderr.write( "\n--ERROR  Input matrix number columns= "+str(lenRow1)+" in first row and the second row= "+str(lenAllRows)+" mismatch ")
+                    error= True
+                    sys.err= 6
+            elif (lenRow1 != len(eachRow) and lenRow1+1 != len(eachRow)):
+                    print ("\n--ERROR  Input Row "+ str(countRow)+" number of columns= "+str(len(eachRow))+" is a length mismatch with row 2 length "+str( lenAllRows))
+                    sys.stderr.write ("\n--ERROR  Input Row "+ str(countRow)+" number of columns= "+str(len(eachRow))+" is a length mismatch with row 2 length "+str( lenAllRows))
+                    error= True
+                    sys.err= 7
+            else:
+                inMatrixRowLabels.append(eachRow[0])
+                tmp= re.search('[abcdefghijklmnopqrstuvwxyz]',eachRow[0].lower())
+                try:
+                    if tmp.group(0) == '':  # if doesn't exist then error
+                        tmp= tmp
+                except Exception as e:
+                    print"-+-+- WARNING Row Label at row "+str(countRow)+" value appears to be non-alphanumeric --"+str(eachRow[j])
+                    sys.stderr.write("\n--+-+- WARNING Row Label at row "+str(countRow)+"  value appears to be non-alphanumeric "+str(eachRow[j]))
+                
+            
+            if len(inMatrixColLabels) > 0: 
+                if (inMatrixColLabels[-1] =='') or (inMatrixColLabels[-1] =='\n'): inMatrixColLabels.pop()
+     
+        inMatrixFH.close()
+
+            #print error, lenAllRows, len(eachRow), eachRow[0]
+     except:
+        #inMatrixFH.close()
+        sys.stderr.write(str(traceback.format_exc()))
+        error= True
+    
+     return error,inMatrixRowLabels,inMatrixColLabels
+
+ #+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-
+
+def ValidateHMCorvarFile(covarLabel, covariateFilePath, row_col_cat_contin, inMatrixRowLabels,inMatrixColLabels):           # This sub routine ensures that the slide design input by the user matches a slide design on record
+
+# verify 
+# 1 That covar file labels match the col or row labels 1 to 1
+# 2 That if a continuous covar file that the 2nd field is not all text hard to tell if '-' or 'e exponent'
+# 3 That the length of the covar file matches the row or col length of the input matrix 
+
+    error= True
+    try:
+    
+        covFH= open( covariateFilePath, 'rU')
+        countRow= 0
+
+        error= False
+        
+        for rawRow in covFH:
+            countRow +=1
+            rawRow= rawRow.replace('\n','')
+            eachRow=  rawRow.split('\t')
+            if countRow== 0: print "\nCovariance file info - label ",str(covarLabel)," row/col categorical or continous",row_col_cat_contin," first row ",str(eachrow)
+    
+            if len(eachRow) < 2 and countRow > 1:
+                print("----ERROR Input Row "+str(countRow)+" does not have a label and/or value ")
+                sys.stderr.write("----ERROR Input Row "+str(countRow)+" does not have a label/or and value")
+                error= True
+                sys.err= 8
+                #return error
+            elif len(eachRow) > 1:
+                tmp= re.search('[abcdefghijklmnopqrstuvwxyz]',eachRow[0].lower())
+                try:
+                    if tmp.group(0) == '':  # if doesn't exist then error
+                        tmp= tmp
+                except Exception as e:
+                    print"\n-+-+- WARNING Covariate Label at row "+str(countRow)+" value appears to be non-alphanumeric --", eachRow[0],"--"
+                    sys.stderr.write("\n--+-+- WARNING Row Headers at  row "+str(countRow)+" value appears to be non-alphanumeric --"+str(eachRow[0])+"--")
+                    
+                if not error:
+                    if row_col_cat_contin[-4:] == 'uous':  # verify continuous is number-ish
+                        tmp= re.search('[+-.0123456789eE]',eachRow[1])
+                        try:
+                            if tmp.group(0) == '':
+                                tmp= tmp
+                        except Exception as e:
+                            print("\n-+-+-WARNING Input Row "+str(countRow)+" covariance continuous value appears to be non-numeric --"+ str(eachRow[1])+"--")
+                            sys.stderr.write("\n-+-+-WARNING Input Row "+str(countRow)+" covariance continuous value appears to be non-numeric --"+ str(eachRow[1])+"--")
+                            #error= True
+    except:
+        sys.stderr.write(str(traceback.format_exc()))
+
+    covFH.close()
+
+    return error
+
+
+if __name__ == "__main__":
+    main()
+
+
diff -r e01b833f5d43 -r 16593e40c2cd mda_heatmap_gen.xml
--- a/mda_heatmap_gen.xml	Fri Feb 03 13:20:50 2017 -0500
+++ b/mda_heatmap_gen.xml	Thu Jul 20 15:31:06 2017 -0400
@@ -1,7 +1,8 @@
 <?xml version="1.0" encoding="UTF-8" ?>
-<tool id="mda_heatmap_gen" name="NG-CHM Generator" version="2.0.2">
+<tool id="mda_heatmap_gen" name="NG-CHM Generator" version="2.0.5">
   <description>Create Clustered Heat Maps</description>
-<command interpreter="bash" detect_errors="aggressive">$__tool_directory__/heatmap.sh  '$hmname' '$hmdesc' '$inputmatrix' ${d_rows.rowOrderMethod} ${d_rows.rowDistanceMeasure} ${d_rows.rowAgglomerationMethod} ${d_cols.columnOrderMethod} ${d_cols.columnDistanceMeasure} ${d_cols.columnAgglomerationMethod} $summarymethod '$__tool_directory__' ${d_rows.rowDendroCut} ${d_cols.colDendroCut} $rowDataType $colDataType
+<!-- <command interpreter="python" detect_errors="aggressive">$__tool_directory__/mda_heatmap_gen.py  'Heat_Map_$hmname' '$hmdesc' '$inputmatrix' ${d_rows.rowOrderMethod} ${d_rows.rowDistanceMeasure} ${d_rows.rowAgglomerationMethod} ${d_cols.columnOrderMethod} ${d_cols.columnDistanceMeasure} ${d_cols.columnAgglomerationMethod} $summarymethod '$__tool_directory__' 0 0 labels labels 'None'-->
+   <command interpreter="bash" detect_errors="aggressive">$__tool_directory__/heatmap.sh  "Heat_Map_$hmname" "$hmdesc" '$inputmatrix' ${d_rows.rowOrderMethod} ${d_rows.rowDistanceMeasure} ${d_rows.rowAgglomerationMethod} ${d_cols.columnOrderMethod} ${d_cols.columnDistanceMeasure} ${d_cols.columnAgglomerationMethod} $summarymethod '$__tool_directory__/' 0 0 labels labels 'None'
     #for $op in $operations
        ${op.class_name}
        ${op.repeatinput.file_name}
@@ -13,13 +14,13 @@
       <exit_code range="1:" level="fatal" />
 	</stdio>
   <inputs>
-    <param name="inputmatrix" type="data" format="text" label="Input Matrix" />
-    <param name="hmname" size="20" type="text" value="Heat_Map_name" label="User Defined Heat Map Name"/>
+    <param name="inputmatrix" type="data" format="Tabular" label="Input Matrix" />
+    <param name="hmname" size="20" type="text" value="Heat_Map_name"  label="User Defined Heat Map Name"/>
     <param name="hmdesc" size="100" optional="true" type="text" value="Heat_Map_description" label="User Defined Heat Map Description"/>
     <param name="summarymethod" 	type="select"  label="Data Summarization Method">
-		<option value="average">average</option>
-		<option value="sample">sample</option>
-		<option value="mode">mode</option>
+		<option value="average">Average</option>
+		<option value="sample">Sample</option>
+		<option value="mode">Mode</option>
     </param>
       <conditional name="d_rows">
 	<param name="rowOrderMethod" type="select" label="Row ordering method" help="Choices -- Hierarchical Clustering, Original Order, Random">
@@ -28,69 +29,34 @@
 		<option value="Random">Random</option>	    
 	</param>
         <when value="Hierarchical">
-	<param name="rowDistanceMeasure" type="select"  label="Row Distance Metric" help="euclidean, binary, manhattan, maximum, canberra, minkowski, or correlation">
-		<option value="euclidean">Euclidean</option>
-		<option value="binary">Binary</option>
-		<option value="manhattan">Manhattan</option>
-		<option value="maximum">Maximum</option>
-		<option value="canberra">Canberra</option>	    
-		<option value="minkowski">Minkowski</option>	    
-		<option value="correlation">Correlation</option>	    
-	</param>
-	<param name="rowAgglomerationMethod" type="select"  label="Row Clustering Method" help="Choices: 'average' for Average Linkage, 'complete' for Complete Linkage, 'single' for Single Linkage, 'ward', 'mcquitty', 'median', or 'centroid'.">
-		<option value="average">Average Linkage</option>
-		<option value="complete">Complete Linkage</option>
-		<option value="single">Single Linkage</option>
-		<option value="ward" selected="true">Ward</option>
-		<option value="mcquitty">Mcquitty</option>	    
-		<option value="median">Median</option>	    
-		<option value="centroid">Centroid</option>	    
-	</param>
-            <param name="rowDendroCut" type="select" label="Create row categorical covariate bar based on number of top-level dendrogram clusters" >
-        		<option value="0" selected="true" >None</option>
-        		<option value="2" >2</option>
-        		<option value="3" >3</option>
-        		<option value="4" >4</option>
-        		<option value="5" >5</option>
-        		<option value="6" >6</option>
-        		<option value="7" >7</option>
-        		<option value="8" >8</option>
-        		<option value="9" >9</option>
-        		<option value="10" >10</option>
-            </param>
+			<param name="rowDistanceMeasure" type="select"  label="Row Distance Metric" help="Euclidean, Binary, Manhattan, Maximum, Canberra, Minkowski, or Correlation">
+				<option value="euclidean">Euclidean</option>
+				<option value="binary">Binary</option>
+				<option value="manhattan">Manhattan</option>
+				<option value="maximum">Maximum</option>
+				<option value="canberra">Canberra</option>	    
+				<option value="minkowski">Minkowski</option>	    
+				<option value="correlation">Correlation</option>	    
+			</param>
+			<param name="rowAgglomerationMethod" type="select"  label="Row Clustering Method" help="Choices:  Average Linkage, Complete Linkage,  Single Linkage, 'Ward', 'Mcquitty', 'Median', or 'Centroid'.">
+				<option value="average">Average Linkage</option>
+				<option value="complete">Complete Linkage</option>
+				<option value="single">Single Linkage</option>
+				<option value="ward" selected="true">Ward</option>
+				<option value="mcquitty">Mcquitty</option>	    
+				<option value="median">Median</option>	    
+				<option value="centroid">Centroid</option>	    
+			</param>
         </when>
         <when value="Original">
-		    <param name="rowDistanceMeasure" type="text" size="0"     value="n/a"/>
-		    <param name="rowAgglomerationMethod" type="text" size="0"     value="n/a"/>
-		    <param name="rowDendroCut" size="0"   type="text" value="0"/>
+		    <param name="rowDistanceMeasure" type="text" size="0"   hidden="true"  value="n/a"/>
+		    <param name="rowAgglomerationMethod" type="text" size="0"  hidden="true"   value="n/a"/>
         </when>
         <when value="Random">
-		    <param name="rowDistanceMeasure" type="text" size="0"     value="n/a"/>
-		    <param name="rowAgglomerationMethod" type="text" size="0"     value="n/a"/>
-		    <param name="rowDendroCut" type="text" size="0"    value="0"/>
+		    <param name="rowDistanceMeasure" type="text" size="0" hidden="true"    value="n/a"/>
+		    <param name="rowAgglomerationMethod" type="text" size="0" hidden="true"    value="n/a"/>
         </when>
     </conditional>
-    <param name="rowDataType" type="select" label="Linkouts to row data type info" >
-        <option value="labels" selected="true" >None</option>
-        <option value="bio.probe.affymetrix" >Affymetrix Probe Id</option>
-        <option value="bio.feature.agilent" >Agilent Id</option>
-        <option value="bio.sample.cbioportal" >cBioPortal sample Id</option>
-        <option value="bio.transcript.ensemble" >Ensemble transcript Id</option>
-        <option value="bio.gene.entrez" >Gene Entrez Id</option>
-        <option value="bio.gene.hugo" >Gene HUGO symbol</option>
-        <option value="bio.go" >Gene Ontology (GO) Id</option>
-        <option value="bio.geo.acc" >GEO Accession Id</option>
-        <option value="bio.probe.illumina" >Illumina Probe Id</option>
-        <option value="bio.probe.infinium" >Infinium Probe Id</option>
-        <option value="bio.pathway.mdanderson" >MD Anderson pathway Id</option>
-        <option value="bio.mirna" >miRNA Id</option>
-        <option value="bio.mirna.mimat" >miRNA MIMAT Id</option>
-        <option value="bio.pubmed" >Pubmed Id</option>
-        <option value="bio.pubmed.search" >Pubmed Search Term</option>
-        <option value="scholar" >Scholarly term</option>
-        <option value="bio.gene.unigene" >Unigene CID</option>
-        <option value="bio.protein.uniprot" >UniProt Id</option>
-    </param>    
 	<conditional name="d_cols">
 	<param name="columnOrderMethod" type="select" label="Column ordering method" help="Choices -- Hierarchical Clustering, Original Order, Random">
 		<option value="Hierarchical">Hierarchical Clustering</option>
@@ -98,69 +64,34 @@
 		<option value="Random">Random</option>	    
 	</param>
         <when value="Hierarchical">
-	<param name="columnDistanceMeasure" type="select"  label="Column Distance Metric" help="euclidean, binary, manhattan, maximum, canberra, minkowski, or correlation">
-		<option value="euclidean">Euclidean</option>
-		<option value="binary">Binary</option>
-		<option value="manhattan">Manhattan</option>
-		<option value="maximum">Maximum</option>
-		<option value="canberra">Canberra</option>	    
-		<option value="minkowski">Minkowski</option>	    
-		<option value="correlation">Correlation</option>	    
-	</param>
-	<param name="columnAgglomerationMethod" type="select"  label="Column Clustering Method" help="Choices: 'average' for Average Linkage, 'complete' for Complete Linkage, 'single' for Single Linkage, 'ward', 'mcquitty', 'median', or 'centroid'.">
-		<option value="average">Average Linkage</option>
-		<option value="complete">Complete Linkage</option>
-		<option value="single">Single Linkage</option>
-		<option value="ward" selected="true">Ward</option>
-		<option value="mcquitty">Mcquitty</option>	    
-		<option value="median">Median</option>	    
-		<option value="centroid">Centroid</option>	    
-	</param>
-            <param name="colDendroCut" type="select" label="Create column categorical covariate bar based on number of top-level dendrogram clusters" >
-        		<option value="0" selected="true" >None</option>
-        		<option value="2" >2</option>
-        		<option value="3" >3</option>
-        		<option value="4" >4</option>
-        		<option value="5" >5</option>
-        		<option value="6" >6</option>
-        		<option value="7" >7</option>
-        		<option value="8" >8</option>
-        		<option value="9" >9</option>
-        		<option value="10" >10</option>
-            </param>
+			<param name="columnDistanceMeasure" type="select"  label="Column Distance Metric" help="Euclidean, Binary, Manhattan, Maximum, Canberra, Minkowski, or Correlation">
+				<option value="euclidean">Euclidean</option>
+				<option value="binary">Binary</option>
+				<option value="manhattan">Manhattan</option>
+				<option value="maximum">Maximum</option>
+				<option value="canberra">Canberra</option>	    
+				<option value="minkowski">Minkowski</option>	    
+				<option value="correlation">Correlation</option>	    
+			</param>
+			<param name="columnAgglomerationMethod" type="select"  label="Column Clustering Method" help="Choices:  Average Linkage, Complete Linkage,  Single Linkage, 'Ward', 'Mcquitty', 'Median', or 'Centroid'.">
+				<option value="average">Average Linkage</option>
+				<option value="complete">Complete Linkage</option>
+				<option value="single">Single Linkage</option>
+				<option value="ward" selected="true">Ward</option>
+				<option value="mcquitty">Mcquitty</option>	    
+				<option value="median">Median</option>	    
+				<option value="centroid">Centroid</option>	    
+			</param>
         </when>
         <when value="Original">
-		    <param name="columnDistanceMeasure" type="text" size="0"     value="n/a"/>
-		    <param name="columnAgglomerationMethod" type="text" size="0"     value="n/a"/>
-		    <param name="colDendroCut" type="text" size="0"     value="0"/>
+		    <param name="columnDistanceMeasure" type="text" size="0" hidden="true"    value="n/a"/>
+		    <param name="columnAgglomerationMethod" type="text" size="0"   hidden="true"  value="n/a"/>
         </when>
         <when value="Random">
-		    <param name="columnDistanceMeasure" type="text" size="0"     value="n/a"/>
-		    <param name="columnAgglomerationMethod" type="text" size="0"     value="n/a"/>
-		    <param name="colDendroCut" type="text" size="0"     value="0"/>
+		    <param name="columnDistanceMeasure" type="text" size="0"  hidden="true"   value="n/a"/>
+		    <param name="columnAgglomerationMethod" type="text" size="0" hidden="true"    value="n/a"/>
         </when>
     </conditional>
-    <param name="colDataType" type="select" label="Linkouts to column data type info" >
-        <option value="labels" selected="true" >None</option>
-        <option value="bio.probe.affymetrix" >Affymetrix Probe Id</option>
-        <option value="bio.feature.agilent" >Agilent Id</option>
-        <option value="bio.sample.cbioportal" >cBioPortal sample Id</option>
-        <option value="bio.transcript.ensemble" >Ensemble transcript Id</option>
-        <option value="bio.gene.entrez" >Gene Entrez Id</option>
-        <option value="bio.gene.hugo" >Gene HUGO symbol</option>
-        <option value="bio.go" >Gene Ontology (GO) Id</option>
-        <option value="bio.geo.acc" >GEO Accession Id</option>
-        <option value="bio.probe.illumina" >Illumina Probe Id</option>
-        <option value="bio.probe.infinium" >Infinium Probe Id</option>
-        <option value="bio.pathway.mdanderson" >MD Anderson pathway Id</option>
-        <option value="bio.mirna" >miRNA Id</option>
-        <option value="bio.mirna.mimat" >miRNA MIMAT Id</option>
-        <option value="bio.pubmed" >Pubmed Id</option>
-        <option value="bio.pubmed.search" >Pubmed Search Term</option>
-        <option value="scholar" >Scholarly term</option>
-        <option value="bio.gene.unigene" >Unigene CId</option>
-        <option value="bio.protein.uniprot" >UniProt Id</option>
-    </param>    
     <repeat name="operations" title="Covariate Bars">
         <param name="class_name" size="20" type="text" value="" label="Axis Covariate Name">
            <sanitizer invalid_char="_">
@@ -174,28 +105,28 @@
         </param>
         <param name="repeatinput" type="data" format="text" label="Axis Covariate File"/>
 	<param name="cat" type="select" label="Axis Covariate Type">
-	  <option value="row_categorical" >row categorical</option>
-	  <option value="row_continuous" >row continuous</option>
-	  <option value="column_categorical" >column categorical</option>
-	  <option value="column_continuous" >column continuous</option>
+	  <option value="row_categorical" >Row Categorical</option>
+	  <option value="row_continuous" >Row Continuous</option>
+	  <option value="column_categorical" >Column Categorical</option>
+	  <option value="column_continuous" >Column Continuous</option>
 	</param>
     </repeat>       
   </inputs>
   <outputs>
-    <data name="output" label='${hmname}' format="ngchm"/>
+    <data name="output" label='Heat_Map_$hmname' format="ngchm"/>
   </outputs>
  <tests>
     <test>
       <param name="inputmatrix" value="400x400.txt" />
       <param name="hmname" value="testRun" />
       <param name="$hmdesc" value="validateTool" />
-      <param name="summarymethod" value="average" />
+      <param name="summarymethod" value="Average" />
       <param name="rowOrderMethod" value="Hierarchical" />
-      <param name="rowDistanceMeasure" value="manhattan" />
-      <param name="rowAgglomerationMethod" value="ward" />
+      <param name="rowDistanceMeasure" value="Manhattan" />
+      <param name="rowAgglomerationMethod" value="Ward" />
       <param name="columnOrderMethod" value="Hierarchical" />
-      <param name="columnDistanceMeasure" value="manhattan" />
-      <param name="columnAgglomerationMethod" value="ward" />
+      <param name="columnDistanceMeasure" value="Manhattan" />
+      <param name="columnAgglomerationMethod" value="Ward" />
       <output name="output" file="Galaxy400x400-noCovariates.ngchm" lines_diff="10" />     
 
     </test>
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diff -r e01b833f5d43 -r 16593e40c2cd ngchm-matrix-functional-test-data/._400x400.txt
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diff -r e01b833f5d43 -r 16593e40c2cd ngchm-matrix-functional-test-data/400x400.txt