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1 ################################################################################
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2 #
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3 # MRC FGU Computational Genomics Group
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4 #
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5 # $Id: script_template.py 2871 2010-03-03 10:20:44Z andreas $
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6 #
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7 # Copyright (C) 2009 Andreas Heger
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8 #
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9 # This program is free software; you can redistribute it and/or
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10 # modify it under the terms of the GNU General Public License
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11 # as published by the Free Software Foundation; either version 2
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12 # of the License, or (at your option) any later version.
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13 #
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14 # This program is distributed in the hope that it will be useful,
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15 # but WITHOUT ANY WARRANTY; without even the implied warranty of
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16 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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17 # GNU General Public License for more details.
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18 #
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19 # You should have received a copy of the GNU General Public License
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20 # along with this program; if not, write to the Free Software
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21 # Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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22 #################################################################################
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23 '''
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24 gat-plot - plot results from a gat analysis
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25 ===========================================
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26
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27 :Author: Andreas Heger
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28 :Release: $Id$
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29 :Date: |today|
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30 :Tags: Python
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31
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32 Purpose
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33 -------
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34
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35 This script takes the results of a ``gat-run.py` or ``gat-compare.py``
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36 and plots the results.
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37
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38 This script requires matplotlib.
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39
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40 Usage
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41 -----
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42
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43 Example::
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44
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45 python gat-plot.py --input-filename-results=gat.results.tsv.gz
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46 python gat-plot.py --input-filename-counts=gat.counts.tsv.gz
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47
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48 Type::
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49
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50 python gatplot.py --help
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51
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52 for command line help.
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53
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54 Documentation
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55 -------------
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56
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57 Code
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58 ----
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59
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60 '''
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61
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62 import os, sys, re, optparse, collections, types, glob, time
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63 import numpy
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64
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65 import gat
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66 import gat.Experiment as E
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67 import gat.IOTools as IOTools
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68 import gat.IO as IO
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69
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70 try:
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71 import matplotlib.pyplot as plt
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72 HASPLOT = True
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73 except (ImportError,RuntimeError):
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74 HASPLOT = False
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75
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76 class DummyAnnotatorResult:
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77
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78 format_observed = "%i"
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79 format_expected = "%6.4f"
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80 format_fold = "%6.4f"
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81 format_pvalue = "%6.4e"
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82
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83 def __init__( self ):
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84 pass
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85
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86 @classmethod
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87 def _fromLine( cls, line ):
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88 x = cls()
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89 data = line[:-1].split("\t")
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90 x.track, x.annotation = data[:2]
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91 x.observed, x.expected, x.lower95, x.upper95, x.stddev, x.fold, x.pvalue, x.qvalue = \
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92 map(float, data[2:] )
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93 return x
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94
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95 def __str__(self):
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96 return "\t".join( (self.track,
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97 self.annotation,
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98 self.format_observed % self.observed,
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99 self.format_expected % self.expected,
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100 self.format_expected % self.lower95,
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101 self.format_expected % self.upper95,
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102 self.format_expected % self.stddev,
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103 self.format_fold % self.fold,
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104 self.format_pvalue % self.pvalue,
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105 self.format_pvalue % self.qvalue ) )
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106
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107 def buildPlotFilename( options, key ):
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108 filename = re.sub("%s", key, options.output_plots_pattern)
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109 filename = re.sub("[^a-zA-Z0-9-_./]", "_", filename )
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110 dirname = os.path.dirname( filename )
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111 if dirname and not os.path.exists( dirname ): os.makedirs( dirname )
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112 return filename
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113
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114 def plotBarplots( annotator_results, options ):
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115 '''output a series of bar-plots.
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116
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117 Output for each track.
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118
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119 Significant results are opaque, while
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120 non-significant results are transparent.'''
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121
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122 for track in annotator_results:
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123 plt.figure()
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124 r = annotator_results[track]
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125 keys, values = zip( *r.items())
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126 pos = range(len(r))
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127 bars = plt.barh( pos, [x.fold for x in values] )
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128 for b,v in zip(bars, values):
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129 if v.qvalue > 0.05: b.set_alpha( 0.10 )
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130
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131 filename = buildPlotFilename( options, "bars-%s" % track )
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132 plt.yticks( pos, keys )
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133 plt.axvline( x=1, color="r")
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134 plt.savefig( filename )
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135
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136 def plotBarplot( annotator_results, options ):
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137 '''output a single bar-plots.
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138
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139 Output for each track.
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140
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141 Significant results are opaque, while
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142 non-significant results are transparent.'''
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143
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144 ntracks = len(annotator_results )
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145 height = 1.0 / float(ntracks)
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146
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147 plt.figure()
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148
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149 for trackid, track in enumerate(annotator_results):
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150
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151 r = annotator_results[track]
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152 rr = r.items()
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153 rr.sort()
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154 keys, values = zip(*rr)
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155 pos = numpy.arange(0,len(r),1) + trackid * height
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156 bars = plt.barh( pos,
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157 [x.fold for x in values],
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158 height = height,
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159 label = track,
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160 xerr = [x.stddev / x.expected for x in values],
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161 color = "bryg"[trackid % 4])
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162 for b,v in zip(bars, values):
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163 if v.pvalue > 0.05: b.set_alpha( 0.10 )
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164
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165 pos = range(len(r))
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166
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167 plt.yticks( pos, keys )
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168 plt.axvline(x=1, color = "r" )
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169 filename = buildPlotFilename( options, "bars-all" )
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170 plt.legend()
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171 plt.savefig( filename )
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172
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173 def main( argv = None ):
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174 """script main.
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175
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176 parses command line options in sys.argv, unless *argv* is given.
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177 """
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178
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179 if not argv: argv = sys.argv
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180
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181 # setup command line parser
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182 parser = optparse.OptionParser( version = "%prog version: $Id: script_template.py 2871 2010-03-03 10:20:44Z andreas $",
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183 usage = globals()["__doc__"] )
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184
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185 parser.add_option("-l", "--sample-file", dest="sample_files", type="string", action="append",
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186 help="filename with sample files. Start processing from samples [default=%default]." )
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187
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188 parser.add_option("-o", "--order", dest="output_order", type="choice",
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189 choices = ( "track", "annotation", "fold", "pvalue", "qvalue" ),
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190 help="order results in output by fold, track, etc. [default=%default]." )
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191
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192 parser.add_option("-p", "--pvalue-method", dest="pvalue_method", type="choice",
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193 choices = ( "empirical", "norm", ),
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194 help="type of pvalue reported [default=%default]." )
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195
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196 parser.add_option( "--results-file", dest="input_filename_results", type="string",
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197 help="start processing from results - no segments required [default=%default]." )
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198
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199 parser.add_option( "--output-plots-pattern", dest="output_plots_pattern", type="string",
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200 help="output pattern for plots [default=%default]" )
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201
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202 parser.add_option( "--output-samples-pattern", dest="output_samples_pattern", type="string",
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203 help="output pattern for samples. Samples are stored in bed format, one for "
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204 " each segment [default=%default]" )
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205
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206 parser.add_option( "--plots", dest="plots", type="choice",
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207 choices = ( "all",
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208 "bars-per-track",
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209 "bars", ),
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210 help="plots to be created [default=%default]." )
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211
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212 parser.set_defaults(
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213 sample_files = [],
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214 num_samples = 1000,
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215 output_stats = [],
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216 output_filename_counts = None,
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217 output_order = "fold",
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218 input_filename_results = None,
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219 pvalue_method = "empirical",
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220 output_plots_pattern = None,
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221 )
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222
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223 ## add common options (-h/--help, ...) and parse command line
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224 (options, args) = E.Start( parser, argv = argv, add_output_options = True )
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225
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226 annotator_results = IO.readAnnotatorResults( options.input_filename_results )
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227
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228 if "speparate-bars" in options.plots:
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229 plotBarplots( annotator_results, options )
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230 if "bars" in options.plots:
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231 plotBarplot( annotator_results, options )
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232
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233 ## write footer and output benchmark information.
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234 E.Stop()
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235
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236 if __name__ == "__main__":
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237 sys.exit( main( sys.argv) )
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