view SMART/Java/Python/getWigProfile.py @ 22:1e3f2c2657a3

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author m-zytnicki
date Mon, 29 Apr 2013 03:26:07 -0400
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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
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"""
Cluster the data into regions (defined by size and overlap with next region) and keep only highest peaks.
"""

import math
from optparse import OptionParser
from SMART.Java.Python.structure.TranscriptContainer import TranscriptContainer
from commons.core.parsing.WigParser import WigParser
from SMART.Java.Python.misc.Progress import Progress
from SMART.Java.Python.misc.RPlotter import RPlotter

class GetWigProfile(object):

	def __init__(self, verbosity):
		self.verbosity	= verbosity
		self.values		 = {}
		self.defaultValue = 0.0

	def _iToJ(self, i, size):
		return min(self.nbPoints+1, int(math.floor(float(i - self.distance) / (size) * (self.nbPoints))))

	def readTranscripts(self):
		self.strandNames = (1, -1) if self.strands else (1, )
		self.values		= dict([(strand, dict([(i, 0.0) for i in range(self.nbPoints + 2 * self.distance)])) for strand in self.strandNames])
		transcriptParser = TranscriptContainer(self.inputFileName, self.inputFormat, self.verbosity)
		wigParser		= WigParser(self.wig)
		nbValues		 = dict([(strand, dict([(i, 0.0) for i in range(self.nbPoints + 2 * self.distance)])) for strand in self.strandNames])
		wigParser.setStrands(self.strands)
		wigParser.setDefaultValue(self.defaultValue)

		progress = Progress(transcriptParser.getNbTranscripts(), "Parsing %s" % (self.inputFileName), self.verbosity)
		for transcript in transcriptParser.getIterator():
			transcriptSize = transcript.getSize()
			expectedSize   = transcriptSize + 2 * self.distance
			transcript.extendStart(self.distance)
			transcript.extendEnd(self.distance)
			theseValues = transcript.extractWigData(wigParser)

			if len(self.strandNames) == 1:
				theseValues = {1: theseValues}
			for strand in self.strandNames:
				if len(theseValues[strand]) < expectedSize:
					theseValues[strand] = [self.defaultValue] * (expectedSize - len(theseValues[strand])) + theseValues[strand]
				if len(theseValues[strand]) != expectedSize:
					raise Exception("Got something wrong with the size of the WIG data concerning %s [%s]: %d found instead of %d" % (transcript, ",".join(["%d-%d" % (exon.getStart(), exon.getEnd()) for exon in transcript.getExons()]), len(theseValues[strand]), expectedSize))
				fivePValues = theseValues[strand][: self.distance]
				nbValues         = [0.0] * (self.nbPoints)
				transcriptValues = [0.0] * (self.nbPoints)
				for i in range(self.distance, len(theseValues[strand]) - self.distance):
					startJ = self._iToJ(i, transcriptSize)
					endJ   = max(startJ+1, self._iToJ(i+1, transcriptSize))
					for j in range(startJ, endJ):
						transcriptValues[j]	+= theseValues[strand][i]
						nbValues[j] += 1
				threePValues = theseValues[strand][-self.distance: ]
				values = fivePValues + [self.defaultValue if nbValue == 0 else transcriptValue / nbValue for transcriptValue, nbValue in zip(transcriptValues, nbValues)] + threePValues
				for i, value in enumerate(values):
					self.values[strand][i] += value
			progress.inc()
		progress.done()

		for strand in self.strandNames:
			if strand == 0:
				strand = 1
			for i in range(self.nbPoints + 2 * self.distance):
				self.values[strand][i] /= transcriptParser.getNbTranscripts() * strand


	def smoothen(self):
		if self.smoothenForce == None:
			return
		for strand in self.strandNames:
			averageValues = {}
			for center in range(self.distance, self.distance + self.nbPoints):
				sum		= 0.0
				nbValues = 0.0
				for i in range(center - self.smoothenForce + 1, center + self.smoothenForce):
					if i > self.distance and i < self.distance + self.nbPoints:
						nbValues += 1
						sum		+= self.values[strand][i]
				averageValues[center] = sum / nbValues
			for position in range(self.distance, self.distance + self.nbPoints):
				self.values[strand][position] = averageValues[position]
		

	def plot(self):
		plotter = RPlotter(self.outputFileName, self.verbosity)
		for strand in self.strandNames:
			plotter.addLine(self.values[strand])
		if self.log:
			plotter.setLog("y")
		plotter.setAxisLabel("x", {0: -self.distance, self.distance: "start", self.distance+self.nbPoints-1: "end", 2*self.distance+self.nbPoints-1: self.distance})
		plotter.plot()



if __name__ == "__main__":
	
	# parse command line
	description = "Get WIG Profile v1.0.1: Compute the average profile of some genomic coordinates using WIG files (thus covering a large proportion of the genome). [Category: WIG Tools]"

	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", "--inputFormat", dest="inputFormat",		action="store",											type="string", help="format of the input file [compulsory] [format: transcript file format]")
	parser.add_option("-w", "--wig",				 dest="wig",						action="store",											type="string", help="wig file name [compulsory] [format: file in WIG format]")	
	parser.add_option("-p", "--nbPoints",		 dest="nbPoints",				action="store",			 default=1000,	type="int",		 help="number of points on the x-axis [compulsory] [format: int] [default: 1000]")	
	parser.add_option("-d", "--distance",		 dest="distance",				action="store",			 default=0,			type="int",		 help="distance around genomic coordinates [compulsory] [format: int] [default: 0]")	
	parser.add_option("-s", "--strands",		 dest="strands",				action="store_true", default=False,								 help="consider both strands separately [format: boolean] [default: False]")	
	parser.add_option("-m", "--smoothen",		 dest="smoothen",				action="store",			 default=None,	type="int",		 help="smoothen the curve [format: int] [default: None]")	
	parser.add_option("-a", "--default",		 dest="defaultValue",	 action="store",			 default=0.0,	 type="float",	help="default value (when value is NA) [default: 0.0] [format: float]")
	parser.add_option("-o", "--output",			 dest="outputFileName", action="store",											type="string", help="output file [compulsory] [format: output file in PNG format]")
	parser.add_option("-l", "--log",				 dest="log",						action="store_true", default=False,								 help="use log scale for y-axis	[format: boolean] [default: False]")
	parser.add_option("-v", "--verbosity",	 dest="verbosity",			action="store",			 default=1,			type="int",		 help="trace level [format: int]")
	(options, args) = parser.parse_args()

	wigProfile								= GetWigProfile(options.verbosity)
	wigProfile.strands			 	= options.strands
	wigProfile.inputFileName	= options.inputFileName
	wigProfile.inputFormat		= options.inputFormat
	wigProfile.wig						= options.wig
	wigProfile.nbPoints				= options.nbPoints
	wigProfile.distance				= options.distance
	wigProfile.smoothenForce	= options.smoothen
	wigProfile.defaultValue	  = options.defaultValue
	wigProfile.outputFileName = options.outputFileName
	wigProfile.log						= options.log

	wigProfile.readTranscripts()
	wigProfile.smoothen()
	wigProfile.plot()