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1 #!/usr/bin/env python
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2 """
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3 Author: Timothy Tickle
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4 Description: Make PCoA of an abundance file
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5 """
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6
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7 __author__ = "Timothy Tickle"
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8 __copyright__ = "Copyright 2012"
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9 __credits__ = ["Timothy Tickle"]
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10 __license__ = ""
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11 __version__ = ""
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12 __maintainer__ = "Timothy Tickle"
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13 __email__ = "ttickle@sph.harvard.edu"
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14 __status__ = "Development"
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15
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16 import sys
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17 import argparse
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18 from src.AbundanceTable import AbundanceTable
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19 from src.Metric import Metric
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20 import csv
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21 import os
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22 from src.PCoA import PCoA
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23
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24 #Set up arguments reader
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25 argp = argparse.ArgumentParser( prog = "scriptPcoa.py",
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26 description = """PCoAs an abundance file given a metadata.\nExample:python scriptPcoa.py -i TID -l STSite""" )
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27
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28 #Arguments
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29 #For table
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30 argp.add_argument("-i","--id", dest="sIDName", default="ID", help="Abundance Table ID")
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31 argp.add_argument("-l","--meta", dest="sLastMetadataName", help="Last metadata name")
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32 argp.add_argument("-d","--fDelim", dest= "cFileDelimiter", action= "store", default="\t", help="File delimiter, default tab")
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33 argp.add_argument("-f","--featureDelim", dest="cFeatureNameDelimiter", action= "store", metavar="Feature Name Delimiter", default="|", help="Feature delimiter")
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34
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35 argp.add_argument("-n","--doNorm", dest="fDoNormData", action="store_true", default=False, help="Flag to turn on normalization")
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36 argp.add_argument("-s","--doSum", dest="fDoSumData", action="store_true", default=False, help="Flag to turn on summation")
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37
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38 argp.add_argument("-p","--paint", dest="sLabel", metavar= "Label", default=None, help="Label to paint in the PCoA")
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39 argp.add_argument("-m","--metric", dest="strMetric", metavar = "distance", default = PCoA.c_BRAY_CURTIS, help ="Distance metric to use. Pick from braycurtis, canberra, chebyshev, cityblock, correlation, cosine, euclidean, hamming, spearman, sqeuclidean, unifrac_unweighted, unifrac_weighted")
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40 argp.add_argument("-o","--outputFile", dest="strOutFile", metavar= "outputFile", default=None, help="Specify the path for the output figure.")
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41 argp.add_argument("-D","--DistanceMatrix", dest="strFileDistanceMatrix", metavar= "strFileDistanceMatrix", default=None, help="Specify the path for outputing the distance matrix (if interested). Default this will not output.")
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42 argp.add_argument("-C","--CoordinatesMatrix", dest="strFileCoordinatesMatrix", metavar= "strFileCoordinatesMatrix", default=None, help="Specify the path for outputing the x,y coordinates matrix (Dim 1 and 2). Default this will not output.")
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43
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44 # Unifrac arguments
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45 argp.add_argument("-t","--unifracTree", dest="istrmTree", metavar="UnifracTreeFile", default=None, help="Optional file only needed for UniFrac calculations.")
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46 argp.add_argument("-e","--unifracEnv", dest="istrmEnvr", metavar="UnifracEnvFile", default=None, help="Optional file only needed for UniFrac calculations.")
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47 argp.add_argument("-c","--unifracColor", dest="fileUnifracColor", metavar="UnifracColorFile", default = None, help="A text file indicating the groupings of metadata to color. Each line in the file is a group to color. An example file line would be 'GroupName:ID,ID,ID,ID'")
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48
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49 argp.add_argument("strFileAbund", metavar = "Abundance file", nargs="?", help ="Input data file")
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50
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51 args = argp.parse_args( )
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52
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53 #Read in abundance table
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54 abndTable = None
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55 if args.strFileAbund:
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56 abndTable = AbundanceTable.funcMakeFromFile(args.strFileAbund,
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57 cDelimiter = args.cFileDelimiter,
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58 sMetadataID = args.sIDName,
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59 sLastMetadata = args.sLastMetadataName,
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60 cFeatureNameDelimiter= args.cFeatureNameDelimiter)
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61
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62 #Normalize if need
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63 if args.fDoSumData:
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64 abndTable.funcSumClades()
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65
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66 #Sum if needed
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67 if args.fDoNormData:
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68 abndTable.funcNormalize()
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69
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70 #Get the metadata to paint
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71 lsKeys = None
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72 if abndTable:
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73 lsKeys = abndTable.funcGetMetadataCopy().keys() if not args.sLabel else [args.sLabel]
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74
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75 #Get pieces of output file
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76 if not args.strOutFile:
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77 if not args.strFileAbund:
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78 args.strOutFile = os.path.splitext(os.path.basename(args.istrmEnvr))[0]+"-pcoa.pdf"
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79 else:
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80 args.strOutFile = os.path.splitext(os.path.basename(args.strFileAbund))[0]+"-pcoa.pdf"
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81 lsFilePieces = os.path.splitext(args.strOutFile)
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82
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83 # Make PCoA object
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84 # Get PCoA object and plot
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85 pcoa = PCoA()
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86 if(not args.strMetric in [Metric.c_strUnifracUnweighted,Metric.c_strUnifracWeighted]) and abndTable:
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87 pcoa.loadData(abndTable,True)
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88 # Optional args.strFileDistanceMatrix if not none will force a printing of the distance measures to the path in args.strFileDistanceMatrix
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89 pcoa.run(tempDistanceMetric=args.strMetric, iDims=2, strDistanceMatrixFile=args.strFileDistanceMatrix, istrmTree=args.istrmTree, istrmEnvr=args.istrmEnvr)
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90
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91 # Write dim 1 and 2 coordinates to file
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92 if args.strFileCoordinatesMatrix:
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93 lsIds = pcoa.funcGetIDs()
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94 mtrxCoordinates = pcoa.funcGetCoordinates()
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95 csvrCoordinates = csv.writer(open(args.strFileCoordinatesMatrix, 'w'))
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96 csvrCoordinates.writerow(["ID","Dimension_1","Dimension_2"])
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97 for x in xrange(mtrxCoordinates.shape[0]):
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98 strId = lsIds[x] if lsIds else ""
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99 csvrCoordinates.writerow([strId]+mtrxCoordinates[x].tolist())
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100
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101 # Paint metadata
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102 if lsKeys:
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103 for iIndex in xrange(len(lsKeys)):
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104 lsMetadata = abndTable.funcGetMetadata(lsKeys[iIndex])
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105
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106 pcoa.plotList(lsLabelList = lsMetadata,
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107 strOutputFileName = lsFilePieces[0]+"-"+lsKeys[iIndex]+lsFilePieces[1],
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108 iSize=20,
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109 dAlpha=1.0,
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110 charForceColor=None,
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111 charForceShape=None,
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112 fInvert=False,
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113 iDim1=1,
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114 iDim2=2)
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115
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116 if args.strMetric in [Metric.c_strUnifracUnweighted,Metric.c_strUnifracWeighted]:
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117
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118 c_sNotGiven = "Not_specified"
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119
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120 lsIds = pcoa.funcGetIDs()
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121 lsGroupLabels = [c_sNotGiven for s in lsIds]
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122
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123 if args.fileUnifracColor:
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124
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125 # Read color file and make a dictionary to convert ids
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126 lsColorLines = csv.reader(open(args.fileUnifracColor))
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127 dictConvertIDToGroup = {}
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128 for lsLine in lsColorLines:
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129 if lsLine:
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130 sGroupID, sFirstID = lsLine[0].split(":")
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131 dictConvertIDToGroup.update(dict([(sID,sGroupID) for sID in [sFirstID]+lsLine[1:]]))
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132
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133 lsGroupLabels = [dictConvertIDToGroup.get(sID,c_sNotGiven) for sID in lsIds]
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134
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135 pcoa.plotList(lsLabelList = lsGroupLabels,
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136 strOutputFileName = lsFilePieces[0]+"-"+args.strMetric+lsFilePieces[1],
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137 iSize=20,
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138 dAlpha=1.0,
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139 charForceColor=None,
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140 charForceShape=None,
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141 fInvert=False,
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142 iDim1=1,
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143 iDim2=2)
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