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comparison maaslin-4450aa4ecc84/src/MaaslinToGraphlanAnnotation.py @ 1:a87d5a5f2776

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Uploaded the version running on the prod server
author george-weingart
date Sun, 08 Feb 2015 23:08:38 -0500
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0:e0b5980139d9 1:a87d5a5f2776
1 #!/usr/bin/env python
2 #####################################################################################
3 #Copyright (C) <2012>
4 #
5 #Permission is hereby granted, free of charge, to any person obtaining a copy of
6 #this software and associated documentation files (the "Software"), to deal in the
7 #Software without restriction, including without limitation the rights to use, copy,
8 #modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
9 #and to permit persons to whom the Software is furnished to do so, subject to
10 #the following conditions:
11 #
12 #The above copyright notice and this permission notice shall be included in all copies
13 #or substantial portions of the Software.
14 #
15 #THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
16 #INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
17 #PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
18 #HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
19 #OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
20 #SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
21 #
22 # This file is a component of the MaAsLin (Multivariate Associations Using Linear Models),
23 # authored by the Huttenhower lab at the Harvard School of Public Health
24 # (contact Timothy Tickle, ttickle@hsph.harvard.edu).
25 #####################################################################################
26
27 __author__ = "Timothy Tickle"
28 __copyright__ = "Copyright 2012"
29 __credits__ = ["Timothy Tickle"]
30 __license__ = ""
31 __version__ = ""
32 __maintainer__ = "Timothy Tickle"
33 __email__ = "ttickle@sph.harvard.edu"
34 __status__ = "Development"
35
36 import argparse
37 import csv
38 import math
39 from operator import itemgetter
40 import re
41 import string
42 import sys
43
44 #def funcGetColor(fNumeric,fMax):
45 # if fNumeric>0:
46 # return("#"+str(int(99*fNumeric/fMax)).zfill(2)+"0000")
47 # if fNumeric<0:
48 # return("#00"+str(int(99*abs(fNumeric/fMax))).zfill(2)+"00")
49 # return("#000000")
50
51 def funcGetColor(fNumeric):
52 if fNumeric>0:
53 return sRingPositiveColor
54 else:
55 return sRingNegativeColor
56
57 def funcGetAlpha(fNumeric,fMax):
58 return max(abs(fNumeric/fMax),dMinAlpha)
59
60 #Constants
61 sAnnotation = "annotation"
62 sAnnotationColor = "annotation_background_color"
63 sClass = "class"
64 sRingAlpha = "ring_alpha"
65 dMinAlpha = .075
66 sRingColor = "ring_color"
67 sRingHeight = "ring_height"
68 #sRingHeightMin = 0.5
69 sStandardizedRingHeight = "1.01"
70 sRingLabel = "ring_label"
71 sRingLabelSizeWord = "ring_label_font_size"
72 sRingLabelSize = 10
73 sRingLineColor = "#999999"
74 sRingPositiveWord = "Positive"
75 sRingPositiveColor = "#990000"
76 sRingNegativeWord = "Negative"
77 sRingNegativeColor = "#009900"
78 sRingLineColorWord = "ring_separator_color"
79 sRingLineThickness = "0.5"
80 sRingLineThicknessWord = "ring_internal_separator_thickness"
81 sCladeMarkerColor = "clade_marker_color"
82 sCladeMarkerSize = "clade_marker_size"
83 sHighlightedMarkerSize = "10"
84 c_dMinDoubleValue = 0.00000000001
85
86 #Set up arguments reader
87 argp = argparse.ArgumentParser( prog = "MaaslinToGraphlanAnnotation.py",
88 description = """Converts summary files to graphlan annotation files.""" )
89
90 #### Read in information
91 #Arguments
92 argp.add_argument("strInputSummary", metavar = "SummaryFile", type = argparse.FileType("r"), help ="Input summary file produced by maaslin")
93 argp.add_argument("strInputCore", metavar = "CoreFile", type = argparse.FileType("r"), help ="Core file produced by Graphlan from the maaslin pcl")
94 argp.add_argument("strInputHeader", metavar = "HeaderFile", type = argparse.FileType("r"), help ="Input header file to append to the generated annotation file.")
95 argp.add_argument("strOutputAnnotation", metavar = "AnnotationFile", type = argparse.FileType("w"), help ="Output annotation file for graphlan")
96
97 args = argp.parse_args( )
98
99 #Read in the summary file and transform to class based descriptions
100 csvSum = open(args.strInputSummary,'r') if isinstance(args.strInputSummary, str) else args.strInputSummary
101 fSum = csv.reader(csvSum, delimiter="\t")
102 #Skip header (until i do this a better way)
103 fSum.next()
104
105 #Extract associations (Metadata,taxon,coef,qvalue)
106 lsAssociations = [[sLine[1],sLine[2],sLine[4],sLine[7]] for sLine in fSum]
107 csvSum.close()
108
109 #### Read in default graphlan settings provided by maaslin
110 #Read in the annotation header file
111 csvHdr = open(args.strInputHeader,'r') if isinstance(args.strInputHeader, str) else args.strInputHeader
112 fHdr = csv.reader(csvHdr, delimiter="\t")
113
114 #Begin writting the output
115 #Output annotation file
116 csvAnn = open(args.strOutputAnnotation,'w') if isinstance(args.strOutputAnnotation, str) else args.strOutputAnnotation
117 fAnn = csv.writer(csvAnn, delimiter="\t")
118 fAnn.writerows(fHdr)
119 csvHdr.close()
120
121 #If no associatiosn were found
122 if(len(lsAssociations)==0):
123 csvAnn.close()
124
125 else:
126 #### Fix name formats
127 #Manipulate names to graphlan complient names (clades seperated by .)
128 lsAssociations = sorted(lsAssociations, key=itemgetter(1))
129 lsAssociations = [[sBug[0]]+[re.sub("^[A-Za-z]__","",sBug[1])]+sBug[2:] for sBug in lsAssociations]
130 lsAssociations = [[sBug[0]]+[re.sub("\|*[A-Za-z]__|\|",".",sBug[1])]+sBug[2:] for sBug in lsAssociations]
131
132 #If this is an OTU, append the number and the genus level together for a more descriptive termal name
133 lsAssociationsModForOTU = []
134 for sBug in lsAssociations:
135 lsBug = sBug[1].split(".")
136 if(len(lsBug))> 1:
137 if(lsBug[-1].isdigit()):
138 lsBug[-2]=lsBug[-2]+"_"+lsBug[-1]
139 lsBug = lsBug[0:-1]
140 lsAssociationsModForOTU.append([sBug[0]]+[".".join(lsBug)]+sBug[2:])
141 else:
142 lsAssociationsModForOTU.append([sBug[0]]+[lsBug[0]]+sBug[2:])
143
144 #Extract just class info
145 #lsClassData = [[sLine[2],sClass,sLine[1]] for sLine in fSum]
146
147 ### Make rings
148 #Setup rings
149 dictRings = dict([[enumData[1],enumData[0]] for enumData in enumerate(set([lsData[0] for lsData in lsAssociationsModForOTU]))])
150
151 #Ring graphlan setting: rings represent a metadata that associates with a feature
152 #Rings have a line to help differetiate them
153 lsRingSettings = [[sRingLabel,lsPair[1],lsPair[0]] for lsPair in dictRings.items()]
154 lsRingLineColors = [[sRingLineColorWord,lsPair[1],sRingLineColor] for lsPair in dictRings.items()]
155 lsRingLineThick = [[sRingLineThicknessWord,lsPair[1],sRingLineThickness] for lsPair in dictRings.items()]
156 lsRingLineLabelSize = [[sRingLabelSizeWord,lsPair[1], sRingLabelSize] for lsPair in dictRings.items()]
157
158 #Create coloring for rings color represents the directionality of the relationship
159 dMaxCoef = max([abs(float(sAssociation[2])) for sAssociation in lsAssociationsModForOTU])
160 lsRingColors = [[lsAssociation[1], sRingColor, dictRings[lsAssociation[0]], funcGetColor(float(lsAssociation[2]))] for lsAssociation in lsAssociationsModForOTU]
161 lsRingAlpha = [[lsAssociation[1], sRingAlpha, dictRings[lsAssociation[0]], funcGetAlpha(float(lsAssociation[2]), dMaxCoef)] for lsAssociation in lsAssociationsModForOTU]
162
163 #Create height for rings representing the log tranformed q-value?
164 dMaxQValue = max([-1*math.log(max(float(sAssociation[3]), c_dMinDoubleValue)) for sAssociation in lsAssociationsModForOTU])
165 #lsRingHeights = [[lsAssociation[1], sRingHeight, dictRings[lsAssociation[0]], ((-1*math.log(max(float(lsAssociation[3]), c_dMinDoubleValue)))/dMaxQValue)+sRingHeightMin] for lsAssociation in lsAssociationsModForOTU]
166 lsRingHeights = [[lsAssociation[1], sRingHeight, dictRings[lsAssociation[0]], sStandardizedRingHeight] for lsAssociation in lsAssociationsModForOTU]
167
168 #### Marker
169 # Marker colors (mainly to make legend
170 lsMarkerColors = [[lsAssociation[1], sCladeMarkerColor, funcGetColor(float(lsAssociation[2]))] for lsAssociation in lsAssociationsModForOTU]
171 lsMarkerSizes = [[lsAssociation[1], sCladeMarkerSize, sHighlightedMarkerSize] for lsAssociation in lsAssociationsModForOTU]
172
173 #### Make internal highlights
174 #Highlight the associated clades
175 lsUniqueAssociatedTaxa = sorted(list(set([lsAssociation[1] for lsAssociation in lsAssociationsModForOTU])))
176
177 lsHighlights = []
178 sABCPrefix = ""
179 sListABC = string.ascii_lowercase
180 iListABCIndex = 0
181 for lsHighlight in lsUniqueAssociatedTaxa:
182 lsTaxa = lsHighlight.split(".")
183 sLabel = sABCPrefix+sListABC[iListABCIndex]+":"+lsTaxa[-1] if len(lsTaxa) > 2 else lsTaxa[-1]
184 lsHighlights.append([lsHighlight, sAnnotation, sLabel])
185 iListABCIndex = iListABCIndex + 1
186 if iListABCIndex > 25:
187 iListABCIndex = 0
188 sABCPrefix = sABCPrefix + sListABC[len(sABCPrefix)]
189
190 #Read in the core file
191 csvCore = open(args.strInputCore,'r') if isinstance(args.strInputCore, str) else args.strInputCore
192 fSum = csv.reader(csvCore, delimiter="\t")
193
194 #Add in all phylum just incase they were not already included here
195 lsAddSecondLevel = list(set([sUnique[0].split(".")[1] for sUnique in fSum if len(sUnique[0].split(".")) > 1]))
196 lsHighlights.extend([[sSecondLevel, sAnnotation, sSecondLevel] for sSecondLevel in lsAddSecondLevel])
197 lsHighlightColor = [[lsHighlight[0], sAnnotationColor,"b"] for lsHighlight in lsHighlights]
198
199 #### Write the remaining output annotation file
200 fAnn.writerows(lsRingSettings)
201 fAnn.writerows(lsRingLineColors)
202 fAnn.writerows(lsRingColors)
203 fAnn.writerows(lsRingAlpha)
204 fAnn.writerows(lsRingLineThick)
205 fAnn.writerows(lsRingLineLabelSize)
206 fAnn.writerows(lsRingHeights)
207 fAnn.writerows(lsMarkerColors)
208 fAnn.writerows(lsMarkerSizes)
209 fAnn.writerows([[sRingPositiveWord, sCladeMarkerColor, sRingPositiveColor]])
210 fAnn.writerows([[sRingNegativeWord, sCladeMarkerColor, sRingNegativeColor]])
211 fAnn.writerows(lsHighlights)
212 fAnn.writerows(lsHighlightColor)
213 csvAnn.close()