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comparison galaxy_micropita/src/breadcrumbs/scripts/scriptManipulateTable.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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1 #!/usr/bin/env python
2 """
3 Author: Timothy Tickle
4 Description: Performs common manipulations on tables
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 argparse
17 import csv
18 import sys
19 import re
20 import os
21 import numpy as np
22 from src.AbundanceTable import AbundanceTable
23 #from src.PCA import PCA
24 from src.ValidateData import ValidateData
25
26 #Set up arguments reader
27 argp = argparse.ArgumentParser( prog = "scriptManipulateTable.py",
28 description = """Performs common manipulations on tables.\nExample: python scriptManipulateTable.py -i TID -l STSite Test.pcl""" )
29
30 #Arguments
31 #Describe table
32 argp.add_argument("-i","--id", dest="sIDName", default="ID", help="Abundance Table ID")
33 argp.add_argument("-l","--meta", dest="sLastMetadataName", help="Last metadata name")
34 argp.add_argument("-d","--fileDelim", dest= "cFileDelimiter", action= "store", default="\t", help="File delimiter, default tab")
35 argp.add_argument("-f","--featureDelim", dest= "cFeatureDelimiter", action= "store", default="|", help="Feature (eg. bug or function) delimiter, default '|'")
36
37 #Checked x 2
38 argp.add_argument("-n","--doNorm", dest="fNormalize", action="store_true", default=False, help="Flag to turn on normalization")
39 argp.add_argument("-s","--doSum", dest="fSum", action="store_true", default=False, help="Flag to turn on summation")
40
41 #Unsupervised filtering
42 argp.add_argument("-A","--doFilterAbundance", dest="strFilterAbundance", action="store", default=None, help="Turns on filtering by abundance (remove features that do not have a minimum abundance in a minimum number of samples); Should be a real number and an integer in the form 'minAbundance,minSamples', (should be performed on a normalized file).")
43 argp.add_argument("-P","--doFilterPercentile", dest="strFilterPercentile", action="store", default=None, help="Turns on filtering by percentile Should be two numbers between 0 and 1 in the form 'percentile,percentage'. (should be performed on a normalized file).")
44 argp.add_argument("-O","--doFilterOccurrence", dest="strFilterOccurence", action="store", default=None, help="Turns on filtering by occurrence. Should be two integers in the form 'minSequence,minSample' (should NOT be performed on a normalized file).")
45 #argp.add_argument("-D","--doFilterDeviation", dest="dCuttOff", action="store", type=float, default=None, help="Flag to turn on filtering by standard deviation (should NOT be performed on a normalized file).")
46
47 #Change bug membership
48 argp.add_argument("-t","--makeTerminal", dest="fMakeTerminal", action="store_true", default=False, help="Works reduces the file to teminal features in the original file.")
49 argp.add_argument("-u","--reduceOTUs", dest="fRemoveOTUs", action="store_true", default=False, help="Remove otu entries from file.")
50 argp.add_argument("-c","--reduceToClade", dest="iClade", action="store", type=int, default=None, help="Specify a level of clade to reduce to [].")
51 argp.add_argument("-b","--reduceToFeatures", dest="strFeatures", action="store", default=None, help="Reduce measurements to certain features (bugs or functions). This can be a comma delimited string (of atleast 2 bugs) or a file.")
52
53 #Manipulate based on metadata
54 #Checked
55 argp.add_argument("-y","--stratifyBy", dest="strStratifyBy", action="store", default=None, help="Metadata to stratify tables by.")
56 argp.add_argument("-r","--removeMetadata", dest="strRemoveMetadata", action="store", default=None, help="Remove samples of this metadata and value (format comma delimited string with metadata id first and the values to remove after 'id,lvalue1,value2').")
57
58 #Manipulate lineage
59 #Checked
60 argp.add_argument("-x","--doPrefixClades", dest="fPrefixClades", action="store_true", default=False, help="Flag to turn on adding prefixes to clades to better identify them, for example s__ will be placed infront of each species.")
61
62 #Combine tables
63 #argp.add_argument("-m","--combineIntersect", dest="fCombineIntersect", action="store_true", default=False, help="Combine two tables including only common features/metadata (intersection).")
64 #argp.add_argument("-e","--combineUnion", dest="fCombineUnion", action="store_true", default=False, help="Combine two tables (union).")
65
66 #Dimensionality Reduction
67 #argp.add_argument("-p","--doPCA", dest="fDoPCA",action="store_true", default=False, help="Flag to turn on adding metabugs and metametadata by performing PCA on each of bug relative abundance and continuous metadata and add the resulting components")
68
69 #Checked
70 argp.add_argument("-o","--output", dest="strOutFile", action="store", default=None, help="Indicate output pcl file.")
71 argp.add_argument("strFileAbund", help ="Input data file")
72
73 args = argp.parse_args( )
74
75 # Creat output file if needed.
76 if not args.strOutFile:
77 args.strOutFile = os.path.splitext(args.strFileAbund)[0]+"-mod.pcl"
78 lsPieces = os.path.splitext(args.strOutFile)
79
80 #List of abundance tables
81 lsTables = []
82
83 #Read in abundance table
84 abndTable = AbundanceTable.funcMakeFromFile(xInputFile=args.strFileAbund,
85 cDelimiter = args.cFileDelimiter,
86 sMetadataID = args.sIDName,
87 sLastMetadata = args.sLastMetadataName,
88 lOccurenceFilter = None,
89 cFeatureNameDelimiter=args.cFeatureDelimiter,
90 xOutputFile = args.strOutFile)
91
92 #TODO Check filtering, can not have some filtering together
93
94 # Make feature list
95 lsFeatures = []
96 if args.strFeatures:
97 print "Get features not completed"
98 # if "," in args.strFeatures:
99 # lsFeatures = args.strFeatures.split(",")
100 # print "ManipulateTable::Reading in feature list "+str(len(lsFeatures))+"."
101 # else:
102 # csvr = csv.reader(open(args.strFeatures, "rU"))
103 # print "ManipulateTable::Reading in feature file "+args.strFeatures+"."
104 # for lsLine in csvr:
105 # lsFeatures.extend(lsLine)
106
107 lsTables.append(abndTable)
108
109 # Do summing
110 #Sum if need
111 if args.fSum:
112 for abndTable in lsTables:
113 print "ManipulateTable::"+abndTable.funcGetName()+" had "+str(len(abndTable.funcGetFeatureNames()))+" features before summing."
114 fResult = abndTable.funcSumClades()
115 if fResult:
116 print "ManipulateTable::"+abndTable.funcGetName()+" was summed."
117 print "ManipulateTable::"+abndTable.funcGetName()+" has "+str(len(abndTable.funcGetFeatureNames()))+" features after summing."
118 else:
119 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" was NOT summed."
120
121 # Filter on counts
122 if args.strFilterOccurence:
123 iMinimumSequence,iMinimumSample = args.strFilterOccurence.split(",")
124 for abndTable in lsTables:
125 if abndTable.funcIsNormalized():
126 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" is normalized and can not be filtered by occurence. This filter needs counts."
127 else:
128 fResult = abndTable.funcFilterAbundanceBySequenceOccurence(iMinSequence = int(iMinimumSequence), iMinSamples = int(iMinimumSample))
129 if fResult:
130 print "ManipulateTable::"+abndTable.funcGetName()+" was filtered by occurence and now has "+str(len(abndTable.funcGetFeatureNames()))+" features."
131 else:
132 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" was NOT filtered by occurence."
133
134 # Change bug membership
135 if args.fMakeTerminal:
136 lsTerminalTables = []
137 for abndTable in lsTables:
138 print "ManipulateTable::"+abndTable.funcGetName()+" had "+str(len(abndTable.funcGetFeatureNames()))+" features before making terminal."
139 abndTable = abndTable.funcGetFeatureAbundanceTable(abndTable.funcGetTerminalNodes())
140 if abndTable:
141 print "ManipulateTable::"+abndTable.funcGetName()+" has "+str(len(abndTable.funcGetFeatureNames()))+" terminal features."
142 lsTerminalTables.append(abndTable)
143 else:
144 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" was not made terminal."
145 lsTables = lsTerminalTables
146
147 if args.fRemoveOTUs:
148 lsNotOTUs = []
149 for abndTable in lsTables:
150 print "ManipulateTable::"+abndTable.funcGetName()+" had "+str(len(abndTable.funcGetFeatureNames()))+" features before removing OTUs."
151 abndTable = abndTable.funcGetWithoutOTUs()
152 if abndTable:
153 print "ManipulateTable::"+abndTable.funcGetName()+" had OTUs removed and now has "+str(len(abndTable.funcGetFeatureNames()))+" features."
154 lsNotOTUs.append(abndTable)
155 else:
156 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" OTUs were not removed."
157 lsTables = lsNotOTUs
158
159 if args.iClade:
160 for abndTable in lsTables:
161 fResult = abndTable.funcReduceFeaturesToCladeLevel(args.iClade)
162 if fResult:
163 print "ManipulateTable::"+abndTable.funcGetName()+" was reduced to clade level "+str(args.iClade)+"."
164 else:
165 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" was NOT reduced in clade levels."
166
167 if args.strFeatures:
168 for abndTable in lsTables:
169 fResult = abndTable.funcGetFeatureAbundanceTable(lsFeatures)
170 if fResult:
171 print "ManipulateTable::"+abndTable.funcGetName()+" has been reduced to given features and now has "+str(len(abndTable.funcGetFeatureNames()))+" features."
172 else:
173 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" could not be reduced to the given list."
174
175 if args.strRemoveMetadata:
176 lsMetadata = args.strRemoveMetadata.split(",")
177 for abndTable in lsTables:
178 fResult = abndTable.funcRemoveSamplesByMetadata(sMetadata=lsMetadata[0], lValuesToRemove=lsMetadata[1:])
179 if fResult:
180 print "ManipulateTable::"+abndTable.funcGetName()+" has had samples removed and now has "+str(len(abndTable.funcGetSampleNames()))+" samples."
181 else:
182 print "ManipulateTable::ERROR. Could not remove samples from "+abndTable.funcGetName()+"."
183
184 # Normalize if needed
185 if args.fNormalize:
186 for abndTable in lsTables:
187 fResult = abndTable.funcNormalize()
188 if fResult:
189 print "ManipulateTable::"+abndTable.funcGetName()+" was normalized."
190 else:
191 print "ManipulateTable::"+abndTable.funcGetName()+" was NOT normalized."
192
193 # Filter on percentile
194 if args.strFilterPercentile:
195 dPercentile,dPercentage = args.strFilterPercentile.split(",")
196 for abndTable in lsTables:
197 if abndTable.funcIsNormalized():
198 fResult = abndTable.funcFilterAbundanceByPercentile(dPercentileCutOff = float(dPercentile), dPercentageAbovePercentile = float(dPercentage))
199 if fResult:
200 print "ManipulateTable::"+abndTable.funcGetName()+" has been reduced by percentile and now has "+str(len(abndTable.funcGetFeatureNames()))+" features."
201 else:
202 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" could not be reduced by percentile."
203 else:
204 print "ManipulateTable::"+abndTable.funcGetName()+" was NOT normalized and so the percentile filter is invalid, please indicate to normalize the table."
205
206 # Filter on abundance (should go after filter on percentile because the filter on percentile
207 # needs the full distribution of features in a sample
208 if args.strFilterAbundance:
209 dAbundance,iMinSamples = args.strFilterAbundance.split(",")
210 dAbundance = float(dAbundance)
211 iMinSamples = int(iMinSamples)
212 for abndTable in lsTables:
213 if abndTable.funcIsNormalized():
214 fResult = abndTable.funcFilterAbundanceByMinValue(dMinAbundance=dAbundance,iMinSamples=iMinSamples)
215 if fResult:
216 print "ManipulateTable::"+abndTable.funcGetName()+" has been reduced by minimum relative abundance value and now has "+str(len(abndTable.funcGetFeatureNames()))+" features."
217 else:
218 print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" could not be reduced by percentile."
219 else:
220 print "ManipulateTable::"+abndTable.funcGetName()+" was NOT normalized and so the abundance filter is invalid, please indicate to normalize the table."
221
222 #if args.dCuttOff:
223 # print "Standard deviation filtering not completed"
224 # for abndTable in lsTables:
225 # abndTable.funcFilterFeatureBySD(dMinSDCuttOff=args.dCuttOff)
226 # if fResult:
227 # print "ManipulateTable::"+abndTable.funcGetName()+" has been reduced by standard deviation and now has "+str(len(abndTable.funcGetFeatureNames()))+" features."
228 # else:
229 # print "ManipulateTable::ERROR. "+abndTable.funcGetName()+" could not be reduced by standard devation."
230
231 # Need to normalize again after abundance data filtering given removing features breaks the normalization
232 # This happends twice because normalization is required to make the abundance data to filter on ;-)
233 # Normalize if needed
234 if args.fNormalize:
235 for abndTable in lsTables:
236 fResult = abndTable.funcNormalize()
237 if fResult:
238 print "ManipulateTable::"+abndTable.funcGetName()+" was normalized after filtering on abundance data."
239
240 #Manipulate lineage
241 if args.fPrefixClades:
242 for abndTable in lsTables:
243 fResult = abndTable.funcAddCladePrefixToFeatures()
244 if fResult:
245 print "ManipulateTable::Clade Prefix was added to "+abndTable.funcGetName()
246 else:
247 print "ManipulateTable::ERROR. Clade Prefix was NOT added to "+abndTable.funcGetName()
248
249 # Under development
250 # Reduce dimensionality
251 #if args.fDoPCA:
252 # pcaCur = PCA()
253 # for abndTable in lsTables:
254 #
255 # # Add data features
256 # # Make data components and add to abundance table
257 # pcaCur.loadData(abndTable,True)
258 # pcaCur.run(fASTransform=True)
259 # ldVariance = pcaCur.getVariance()
260 # lldComponents = pcaCur.getComponents()
261 # # Make Names
262 # lsNamesData = ["Data_PC"+str((tpleVariance[0]+1))+"_"+re.sub("[\.|-]","_",str(tpleVariance[1])) for tpleVariance in enumerate(ldVariance)]
263 # abndTable.funcAddDataFeature(lsNamesData,lldComponents)
264 #
265 # # Add metadata features
266 # # Convert metadata to an input for PCA
267 # pcaCur.loadData(pcaCur.convertMetadataForPCA(abndTable),False)
268 # fSuccessful = pcaCur.run(fASTransform=False)
269 # if(fSuccessful):
270 # ldVariance = pcaCur.getVariance()
271 # lldComponents = pcaCur.getComponents()
272 # # Make Names
273 # lsNamesMetadata = ["Metadata_PC"+str((tpleVariance[0]+1))+"_"+re.sub("[\.|-]","_",str(tpleVariance[1])) for tpleVariance in enumerate(ldVariance)]
274 # # Make metadata components and add to abundance
275 # llsMetadata = [list(npdRow) for npdRow in lldComponents]
276 # abndTable.funcAddMetadataFeature(lsNamesMetadata, llsMetadata)
277 # else:
278 # print "ManipulateTable::No metadata to PCA, no PCA components added to file based on metadata"
279
280 #Manipulate based on metadata
281 if args.strStratifyBy:
282 labndStratifiedTables = []
283 for abndTable in lsTables:
284 labndResult = abndTable.funcStratifyByMetadata(strMetadata=args.strStratifyBy)
285 print "ManipulateTable::"+abndTable.funcGetName()+" was stratified by "+args.strStratifyBy+" in to "+str(len(labndResult))+" tables."
286 labndStratifiedTables.extend(labndResult)
287 lsTables = labndStratifiedTables
288
289 if len(lsTables) == 1:
290 lsTables[0].funcWriteToFile(args.strOutFile)
291 else:
292 iIndex = 1
293 for abndManTable in lsTables:
294 abndManTable.funcWriteToFile(lsPieces[0]+str(iIndex)+lsPieces[1])
295 iIndex = iIndex + 1