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comparison galaxy_micropita/src/breadcrumbs/scripts/scriptPcoa.py @ 3:8fb4630ab314 draft default tip

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author sagun98
date Thu, 03 Jun 2021 17:07:36 +0000
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2:1c5736dc85ab 3:8fb4630ab314
1 #!/usr/bin/env python
2 """
3 Author: Timothy Tickle
4 Description: Make PCoA of an abundance file
5 """
6
7 __author__ = "Timothy Tickle"
8 __copyright__ = "Copyright 2012"
9 __credits__ = ["Timothy Tickle"]
10 __license__ = ""
11 __version__ = ""
12 __maintainer__ = "Timothy Tickle"
13 __email__ = "ttickle@sph.harvard.edu"
14 __status__ = "Development"
15
16 import sys
17 import argparse
18 from src.AbundanceTable import AbundanceTable
19 from src.Metric import Metric
20 import csv
21 import os
22 from src.PCoA import PCoA
23
24 #Set up arguments reader
25 argp = argparse.ArgumentParser( prog = "scriptPcoa.py",
26 description = """PCoAs an abundance file given a metadata.\nExample:python scriptPcoa.py -i TID -l STSite""" )
27
28 #Arguments
29 #For table
30 argp.add_argument("-i","--id", dest="sIDName", default="ID", help="Abundance Table ID")
31 argp.add_argument("-l","--meta", dest="sLastMetadataName", help="Last metadata name")
32 argp.add_argument("-d","--fDelim", dest= "cFileDelimiter", action= "store", default="\t", help="File delimiter, default tab")
33 argp.add_argument("-f","--featureDelim", dest="cFeatureNameDelimiter", action= "store", metavar="Feature Name Delimiter", default="|", help="Feature delimiter")
34
35 argp.add_argument("-n","--doNorm", dest="fDoNormData", action="store_true", default=False, help="Flag to turn on normalization")
36 argp.add_argument("-s","--doSum", dest="fDoSumData", action="store_true", default=False, help="Flag to turn on summation")
37
38 argp.add_argument("-p","--paint", dest="sLabel", metavar= "Label", default=None, help="Label to paint in the PCoA")
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")
40 argp.add_argument("-o","--outputFile", dest="strOutFile", metavar= "outputFile", default=None, help="Specify the path for the output figure.")
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.")
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.")
43
44 # Unifrac arguments
45 argp.add_argument("-t","--unifracTree", dest="istrmTree", metavar="UnifracTreeFile", default=None, help="Optional file only needed for UniFrac calculations.")
46 argp.add_argument("-e","--unifracEnv", dest="istrmEnvr", metavar="UnifracEnvFile", default=None, help="Optional file only needed for UniFrac calculations.")
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'")
48
49 argp.add_argument("strFileAbund", metavar = "Abundance file", nargs="?", help ="Input data file")
50
51 args = argp.parse_args( )
52
53 #Read in abundance table
54 abndTable = None
55 if args.strFileAbund:
56 abndTable = AbundanceTable.funcMakeFromFile(args.strFileAbund,
57 cDelimiter = args.cFileDelimiter,
58 sMetadataID = args.sIDName,
59 sLastMetadata = args.sLastMetadataName,
60 cFeatureNameDelimiter= args.cFeatureNameDelimiter)
61
62 #Normalize if need
63 if args.fDoSumData:
64 abndTable.funcSumClades()
65
66 #Sum if needed
67 if args.fDoNormData:
68 abndTable.funcNormalize()
69
70 #Get the metadata to paint
71 lsKeys = None
72 if abndTable:
73 lsKeys = abndTable.funcGetMetadataCopy().keys() if not args.sLabel else [args.sLabel]
74
75 #Get pieces of output file
76 if not args.strOutFile:
77 if not args.strFileAbund:
78 args.strOutFile = os.path.splitext(os.path.basename(args.istrmEnvr))[0]+"-pcoa.pdf"
79 else:
80 args.strOutFile = os.path.splitext(os.path.basename(args.strFileAbund))[0]+"-pcoa.pdf"
81 lsFilePieces = os.path.splitext(args.strOutFile)
82
83 # Make PCoA object
84 # Get PCoA object and plot
85 pcoa = PCoA()
86 if(not args.strMetric in [Metric.c_strUnifracUnweighted,Metric.c_strUnifracWeighted]) and abndTable:
87 pcoa.loadData(abndTable,True)
88 # Optional args.strFileDistanceMatrix if not none will force a printing of the distance measures to the path in args.strFileDistanceMatrix
89 pcoa.run(tempDistanceMetric=args.strMetric, iDims=2, strDistanceMatrixFile=args.strFileDistanceMatrix, istrmTree=args.istrmTree, istrmEnvr=args.istrmEnvr)
90
91 # Write dim 1 and 2 coordinates to file
92 if args.strFileCoordinatesMatrix:
93 lsIds = pcoa.funcGetIDs()
94 mtrxCoordinates = pcoa.funcGetCoordinates()
95 csvrCoordinates = csv.writer(open(args.strFileCoordinatesMatrix, 'w'))
96 csvrCoordinates.writerow(["ID","Dimension_1","Dimension_2"])
97 for x in xrange(mtrxCoordinates.shape[0]):
98 strId = lsIds[x] if lsIds else ""
99 csvrCoordinates.writerow([strId]+mtrxCoordinates[x].tolist())
100
101 # Paint metadata
102 if lsKeys:
103 for iIndex in xrange(len(lsKeys)):
104 lsMetadata = abndTable.funcGetMetadata(lsKeys[iIndex])
105
106 pcoa.plotList(lsLabelList = lsMetadata,
107 strOutputFileName = lsFilePieces[0]+"-"+lsKeys[iIndex]+lsFilePieces[1],
108 iSize=20,
109 dAlpha=1.0,
110 charForceColor=None,
111 charForceShape=None,
112 fInvert=False,
113 iDim1=1,
114 iDim2=2)
115
116 if args.strMetric in [Metric.c_strUnifracUnweighted,Metric.c_strUnifracWeighted]:
117
118 c_sNotGiven = "Not_specified"
119
120 lsIds = pcoa.funcGetIDs()
121 lsGroupLabels = [c_sNotGiven for s in lsIds]
122
123 if args.fileUnifracColor:
124
125 # Read color file and make a dictionary to convert ids
126 lsColorLines = csv.reader(open(args.fileUnifracColor))
127 dictConvertIDToGroup = {}
128 for lsLine in lsColorLines:
129 if lsLine:
130 sGroupID, sFirstID = lsLine[0].split(":")
131 dictConvertIDToGroup.update(dict([(sID,sGroupID) for sID in [sFirstID]+lsLine[1:]]))
132
133 lsGroupLabels = [dictConvertIDToGroup.get(sID,c_sNotGiven) for sID in lsIds]
134
135 pcoa.plotList(lsLabelList = lsGroupLabels,
136 strOutputFileName = lsFilePieces[0]+"-"+args.strMetric+lsFilePieces[1],
137 iSize=20,
138 dAlpha=1.0,
139 charForceColor=None,
140 charForceShape=None,
141 fInvert=False,
142 iDim1=1,
143 iDim2=2)