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1 #! /usr/bin/env python
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2 #
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3 # Copyright INRA-URGI 2009-2010
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4 #
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5 # This software is governed by the CeCILL license under French law and
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6 # abiding by the rules of distribution of free software. You can use,
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7 # modify and/ or redistribute the software under the terms of the CeCILL
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8 # license as circulated by CEA, CNRS and INRIA at the following URL
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9 # "http://www.cecill.info".
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10 #
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11 # As a counterpart to the access to the source code and rights to copy,
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12 # modify and redistribute granted by the license, users are provided only
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13 # with a limited warranty and the software's author, the holder of the
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14 # economic rights, and the successive licensors have only limited
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15 # liability.
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16 #
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17 # In this respect, the user's attention is drawn to the risks associated
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18 # with loading, using, modifying and/or developing or reproducing the
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19 # software by the user in light of its specific status of free software,
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20 # that may mean that it is complicated to manipulate, and that also
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21 # therefore means that it is reserved for developers and experienced
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22 # professionals having in-depth computer knowledge. Users are therefore
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23 # encouraged to load and test the software's suitability as regards their
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24 # requirements in conditions enabling the security of their systems and/or
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25 # data to be ensured and, more generally, to use and operate it in the
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26 # same conditions as regards security.
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27 #
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28 # The fact that you are presently reading this means that you have had
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29 # knowledge of the CeCILL license and that you accept its terms.
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30 #
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31 from commons.core.writer.WriterChooser import WriterChooser
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32 """Clusterize a set of transcripts"""
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33
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34 import os, os.path, random
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35 from optparse import OptionParser
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60
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36 from heapq import heappush, heappop
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36
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37 from commons.core.parsing.ParserChooser import ParserChooser
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38 from commons.core.writer.Gff3Writer import Gff3Writer
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39 from SMART.Java.Python.structure.Transcript import Transcript
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40 from SMART.Java.Python.ncList.NCListFilePickle import NCListFileUnpickle
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41 from SMART.Java.Python.ncList.FileSorter import FileSorter
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42 from SMART.Java.Python.misc.Progress import Progress
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43 from SMART.Java.Python.misc.UnlimitedProgress import UnlimitedProgress
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44
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45 class Clusterize(object):
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46
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47 def __init__(self, verbosity):
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60
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48 self.parsers = {}
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49 self.sortedFileNames = {}
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50 self.normalize = False
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51 self.presorted = False
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52 self.distance = 1
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53 self.collinear = False
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54 self.nbWritten = 0
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55 self.nbMerges = 0
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56 self.verbosity = verbosity
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36
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57 self.splittedFileNames = {}
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60
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58 self.chromosomes = set()
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59
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60 def __del__(self):
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60
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61 for fileName1 in self.splittedFileNames:
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62 for fileName2 in self.splittedFileNames[fileName1].values():
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63 os.remove(fileName2)
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64
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60
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65 def setInputFiles(self, fileNames, format):
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66 parserChooser = ParserChooser(self.verbosity)
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67 parserChooser.findFormat(format)
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60
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68 for fileName in fileNames:
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69 self.parsers[fileName] = parserChooser.getParser(fileName)
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70 self.sortedFileNames[fileName] = "%s_sorted_%d.pkl" % (os.path.splitext(fileName)[0], random.randint(1, 100000))
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71 if "SMARTTMPPATH" in os.environ:
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72 self.sortedFileNames[fileName] = os.path.join(os.environ["SMARTTMPPATH"], os.path.basename(self.sortedFileNames[fileName]))
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73
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74 def setOutputFileName(self, fileName, format="gff3", title="S-MART", feature="transcript", featurePart="exon"):
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75 writerChooser = WriterChooser()
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76 writerChooser.findFormat(format)
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77 self.writer = writerChooser.getWriter(fileName)
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78 self.writer.setTitle(title)
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79 self.writer.setFeature(feature)
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80 self.writer.setFeaturePart(featurePart)
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81
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82 def setDistance(self, distance):
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83 self.distance = distance
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84
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85 def setColinear(self, collinear):
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86 self.collinear = collinear
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87
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88 def setNormalize(self, normalize):
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89 self.normalize = normalize
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90
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91 def setPresorted(self, presorted):
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92 self.presorted = presorted
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93
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94 def _sortFiles(self):
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95 if self.presorted:
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96 return
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60
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97 for fileName, parser in self.parsers.iteritems():
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98 fs = FileSorter(parser, self.verbosity-4)
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99 fs.perChromosome(True)
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100 fs.setPresorted(self.presorted)
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101 fs.setOutputFileName(self.sortedFileNames[fileName])
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102 fs.sort()
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103 self.splittedFileNames[fileName] = fs.getOutputFileNames()
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104 self.nbElementsPerChromosome = fs.getNbElementsPerChromosome()
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105 self.nbElements = fs.getNbElements()
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106 self.chromosomes.update(self.splittedFileNames[fileName].keys())
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107
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60
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108 def _iterate(self):
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109 progress = UnlimitedProgress(10000, "Reading input file", self.verbosity)
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110 transcripts = []
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111 heap = []
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112 parsersSets = []
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113 if self.chromosomes:
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114 parsersSets.append(self.parsers.values())
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115 else:
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116 for chromosome in self.chromosomes:
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117 parsersSets.append([self.splittedFileNames[fileName][chromosome] for fileName in self.splittedFileNames if chromosome in self.splittedFileNames[fileName]])
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118 for parsers in parsersSets:
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119 for parser in parsers:
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120 iterator = parser.getIterator()
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121 for transcript in iterator:
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122 if transcript.__class__.__name__ == "Mapping":
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123 transcript = transcript.getTranscript()
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124 heappush(heap, (transcript.getChromosome(), transcript.getStart(), -transcript.getEnd(), transcript, iterator))
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125 break
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126 while heap:
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127 chromosome, start, end, newTranscript, iterator = heappop(heap)
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128 for transcript in iterator:
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129 if transcript.__class__.__name__ == "Mapping":
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130 transcript = transcript.getTranscript()
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131 heappush(heap, (transcript.getChromosome(), transcript.getStart(), -transcript.getEnd(), transcript, iterator))
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132 break
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133 newTranscripts = []
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134 if newTranscript.__class__.__name__ == "Mapping":
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135 newTranscript = newTranscript.getTranscript()
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136 for oldTranscript in transcripts:
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137 if self._checkOverlap(newTranscript, oldTranscript):
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138 self._merge(newTranscript, oldTranscript)
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139 elif self._checkPassed(newTranscript, oldTranscript):
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140 self._write(oldTranscript)
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141 else:
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142 newTranscripts.append(oldTranscript)
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143 newTranscripts.append(newTranscript)
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144 transcripts = newTranscripts
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145 progress.inc()
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146 for transcript in transcripts:
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147 self._write(transcript)
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148 progress.done()
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149
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150 def _merge(self, transcript1, transcript2):
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151 self.nbMerges += 1
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152 transcript2.setDirection(transcript1.getDirection())
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153 transcript1.merge(transcript2)
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154
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155 def _write(self, transcript):
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156 self.nbWritten += 1
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157 self.writer.addTranscript(transcript)
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158
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159 def _checkOverlap(self, transcript1, transcript2):
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160 if transcript1.getChromosome() != transcript2.getChromosome():
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161 return False
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162 if self.collinear and transcript1.getDirection() != transcript2.getDirection():
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163 return False
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164 if transcript1.getDistance(transcript2) > self.distance:
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165 return False
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166 return True
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167
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168 def _checkPassed(self, transcript1, transcript2):
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169 return ((transcript1.getChromosome() != transcript2.getChromosome()) or (transcript1.getDistance(transcript2) > self.distance))
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170
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171 def run(self):
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172 self._sortFiles()
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173 self._iterate()
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174 self.writer.close()
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175 if self.verbosity > 0:
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176 print "# input: %d" % (self.nbElements)
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177 print "# written: %d (%d%% overlaps)" % (self.nbWritten, 0 if (self.nbElements == 0) else ((float(self.nbWritten) / self.nbElements) * 100))
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178 print "# merges: %d" % (self.nbMerges)
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179
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180
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181 if __name__ == "__main__":
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182 description = "Clusterize v1.0.3: clusterize the data which overlap. [Category: Merge]"
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183
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184 parser = OptionParser(description = description)
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185 parser.add_option("-i", "--inputs", dest="inputFileNames", action="store", type="string", help="input files (separated by commas) [compulsory] [format: string]")
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186 parser.add_option("-f", "--format", dest="format", action="store", type="string", help="format of file [format: transcript file format]")
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187 parser.add_option("-o", "--output", dest="outputFileName", action="store", type="string", help="output file [compulsory] [format: output file in transcript format given by -u]")
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188 parser.add_option("-u", "--outputFormat", dest="outputFormat", action="store", default="gff", type="string", help="output file format [format: transcript file format]")
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189 parser.add_option("-c", "--collinear", dest="collinear", action="store_true", default=False, help="merge collinear transcripts only [format: bool] [default: false]")
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190 parser.add_option("-d", "--distance", dest="distance", action="store", default=0, type="int", help="max. distance between two transcripts to be merged [format: int] [default: 0]")
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191 parser.add_option("-n", "--normalize", dest="normalize", action="store_true", default=False, help="normalize the number of reads per cluster by the number of mappings per read [format: bool] [default: false]")
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192 parser.add_option("-s", "--sorted", dest="sorted", action="store_true", default=False, help="input is already sorted [format: bool] [default: false]")
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193 parser.add_option("-v", "--verbosity", dest="verbosity", action="store", default=1, type="int", help="trace level [format: int] [default: 1]")
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194 (options, args) = parser.parse_args()
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195
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196 c = Clusterize(options.verbosity)
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197 c.setInputFiles(options.inputFileNames.split(","), options.format)
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198 c.setOutputFileName(options.outputFileName, options.outputFormat)
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199 c.setColinear(options.collinear)
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200 c.setDistance(options.distance)
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201 c.setNormalize(options.normalize)
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202 c.setPresorted(options.sorted)
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203 c.run()
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