view smart_toolShed/SMART/Java/Python/clusterize.py @ 0:e0f8dcca02ed

Uploaded S-MART tool. A toolbox manages RNA-Seq and ChIP-Seq data.
author yufei-luo
date Thu, 17 Jan 2013 10:52:14 -0500
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#! /usr/bin/env python
#
# Copyright INRA-URGI 2009-2010
# 
# This software is governed by the CeCILL license under French law and
# abiding by the rules of distribution of free software. You can use,
# modify and/ or redistribute the software under the terms of the CeCILL
# license as circulated by CEA, CNRS and INRIA at the following URL
# "http://www.cecill.info".
# 
# As a counterpart to the access to the source code and rights to copy,
# modify and redistribute granted by the license, users are provided only
# with a limited warranty and the software's author, the holder of the
# economic rights, and the successive licensors have only limited
# liability.
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# In this respect, the user's attention is drawn to the risks associated
# with loading, using, modifying and/or developing or reproducing the
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# The fact that you are presently reading this means that you have had
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from commons.core.writer.WriterChooser import WriterChooser
"""Clusterize a set of transcripts"""

import os
from optparse import OptionParser
from commons.core.parsing.ParserChooser import ParserChooser
from commons.core.writer.Gff3Writer import Gff3Writer
from SMART.Java.Python.structure.Transcript import Transcript
from SMART.Java.Python.ncList.NCListFilePickle import NCListFileUnpickle
from SMART.Java.Python.ncList.FileSorter import FileSorter
from SMART.Java.Python.misc.Progress import Progress

class Clusterize(object):
        
    def __init__(self, verbosity):
        self.normalize         = False
        self.presorted         = False
        self.distance          = 1
        self.colinear          = False
        self.nbWritten         = 0
        self.nbMerges          = 0
        self.verbosity         = verbosity
        self.splittedFileNames = {}

    def __del__(self):
        for fileName in self.splittedFileNames.values():
            os.remove(fileName)

    def setInputFile(self, fileName, format):
        parserChooser = ParserChooser(self.verbosity)
        parserChooser.findFormat(format)
        self.parser = parserChooser.getParser(fileName)
        self.sortedFileName = "%s_sorted.pkl" % (os.path.splitext(fileName)[0])

    def setOutputFileName(self, fileName, format="gff3", title="S-MART", feature="transcript", featurePart="exon"):
        writerChooser = WriterChooser()
        writerChooser.findFormat(format)
        self.writer = writerChooser.getWriter(fileName)
        self.writer.setTitle(title)
        self.writer.setFeature(feature)
        self.writer.setFeaturePart(featurePart)

    def setDistance(self, distance):
        self.distance = distance

    def setColinear(self, colinear):
        self.colinear = colinear

    def setNormalize(self, normalize):
        self.normalize = normalize
        
    def setPresorted(self, presorted):
        self.presorted = presorted

    def _sortFile(self):
        fs = FileSorter(self.parser, self.verbosity-4)
        fs.perChromosome(True)
        fs.setPresorted(self.presorted)
        fs.setOutputFileName(self.sortedFileName)
        fs.sort()
        self.splittedFileNames       = fs.getOutputFileNames()
        self.nbElementsPerChromosome = fs.getNbElementsPerChromosome()
        self.nbElements              = fs.getNbElements()
        
    def _iterate(self, chromosome):
        progress    = Progress(self.nbElementsPerChromosome[chromosome], "Checking chromosome %s" % (chromosome), self.verbosity)
        transcripts = []
        parser      = NCListFileUnpickle(self.splittedFileNames[chromosome], self.verbosity)
        for newTranscript in parser.getIterator():
            newTranscripts = []
            for oldTranscript in transcripts:
                if self._checkOverlap(newTranscript, oldTranscript):
                    self._merge(newTranscript, oldTranscript)
                elif self._checkPassed(newTranscript, oldTranscript):
                    self._write(oldTranscript)
                else:
                    newTranscripts.append(oldTranscript)
            newTranscripts.append(newTranscript)
            transcripts = newTranscripts
            progress.inc()
        for transcript in transcripts:
            self._write(transcript)
        progress.done()

    def _merge(self, transcript1, transcript2):
        self.nbMerges += 1
        transcript2.setDirection(transcript1.getDirection())
        transcript1.merge(transcript2)

    def _write(self, transcript):
        self.nbWritten += 1
        self.writer.addTranscript(transcript)

    def _checkOverlap(self, transcript1, transcript2):
        if self.colinear and transcript1.getDirection() != transcript2.getDirection():
            return False
        if transcript1.getDistance(transcript2) > self.distance:
            return False
        return True

    def _checkPassed(self, transcript1, transcript2):
        return (transcript1.getDistance(transcript2) > self.distance)

    def run(self):
        self._sortFile()
        for chromosome in sorted(self.splittedFileNames.keys()):
            self._iterate(chromosome)
        self.writer.close()
        if self.verbosity > 0:
            print "# input:   %d" % (self.nbElements)
            print "# written: %d (%d%% overlaps)" % (self.nbWritten, 0 if (self.nbElements == 0) else ((float(self.nbWritten) / self.nbElements) * 100))
            print "# merges:  %d" % (self.nbMerges)
        

if __name__ == "__main__":
    description = "Clusterize v1.0.3: clusterize the data which overlap. [Category: Merge]"
    
    parser = OptionParser(description = description)
    parser.add_option("-i", "--input",     dest="inputFileName",  action="store",                     type="string", help="input file [compulsory] [format: file in transcript format given by -f]")
    parser.add_option("-f", "--format",    dest="format",         action="store",                     type="string", help="format of file [format: transcript file format]")
    parser.add_option("-o", "--output",    dest="outputFileName", action="store",                     type="string", help="output file [compulsory] [format: output file in transcript format given by -u]")
    parser.add_option("-u", "--outputFormat", dest="outputFormat", action="store",     default="gff",             type="string", help="output file format [format: transcript file format]")
    parser.add_option("-c", "--colinear",  dest="colinear",       action="store_true", default=False,                help="merge colinear transcripts only [format: bool] [default: false]")
    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]")
    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]")
    parser.add_option("-v", "--verbosity", dest="verbosity",      action="store",      default=1,     type="int",    help="trace level [format: int] [default: 1]")
    (options, args) = parser.parse_args()
        
    c = Clusterize(options.verbosity)
    c.setInputFile(options.inputFileName, options.format)
    c.setOutputFileName(options.outputFileName, options.outputFormat)
    c.setColinear(options.colinear)
    c.setDistance(options.distance)
    c.setNormalize(options.normalize)
    c.run()