annotate tools/multivariate_stats/pca.py @ 1:cdcb0ce84a1b

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author xuebing
date Fri, 09 Mar 2012 19:45:15 -0500
parents 9071e359b9a3
children
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1 #!/usr/bin/env python
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2
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3 from galaxy import eggs
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4 import sys, string
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5 from rpy import *
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6 import numpy
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7
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8 def stop_err(msg):
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9 sys.stderr.write(msg)
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10 sys.exit()
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11
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12 infile = sys.argv[1]
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13 x_cols = sys.argv[2].split(',')
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14 method = sys.argv[3]
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15 outfile = sys.argv[4]
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16 outfile2 = sys.argv[5]
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17
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18 if method == 'svd':
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19 scale = center = "FALSE"
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20 if sys.argv[6] == 'both':
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21 scale = center = "TRUE"
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22 elif sys.argv[6] == 'center':
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23 center = "TRUE"
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24 elif sys.argv[6] == 'scale':
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25 scale = "TRUE"
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26
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27 fout = open(outfile,'w')
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28 elems = []
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29 for i, line in enumerate( file ( infile )):
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30 line = line.rstrip('\r\n')
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31 if len( line )>0 and not line.startswith( '#' ):
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32 elems = line.split( '\t' )
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33 break
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34 if i == 30:
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35 break # Hopefully we'll never get here...
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36
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37 if len( elems )<1:
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38 stop_err( "The data in your input dataset is either missing or not formatted properly." )
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39
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40 x_vals = []
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41
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42 for k,col in enumerate(x_cols):
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43 x_cols[k] = int(col)-1
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44 x_vals.append([])
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45
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46 NA = 'NA'
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47 skipped = 0
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48 for ind,line in enumerate( file( infile )):
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49 if line and not line.startswith( '#' ):
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50 try:
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51 fields = line.strip().split("\t")
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52 valid_line = True
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53 for k,col in enumerate(x_cols):
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54 try:
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55 xval = float(fields[col])
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56 except:
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57 skipped += 1
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58 valid_line = False
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59 break
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60 if valid_line:
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61 for k,col in enumerate(x_cols):
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62 xval = float(fields[col])
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63 x_vals[k].append(xval)
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64 except:
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65 skipped += 1
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66
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67 x_vals1 = numpy.asarray(x_vals).transpose()
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68 dat= r.list(array(x_vals1))
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69
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70 set_default_mode(NO_CONVERSION)
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71 try:
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72 if method == "cor":
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73 pc = r.princomp(r.na_exclude(dat), cor = r("TRUE"))
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74 elif method == "cov":
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75 pc = r.princomp(r.na_exclude(dat), cor = r("FALSE"))
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76 elif method=="svd":
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77 pc = r.prcomp(r.na_exclude(dat), center = r(center), scale = r(scale))
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78 except RException, rex:
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79 stop_err("Encountered error while performing PCA on the input data: %s" %(rex))
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80
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81 set_default_mode(BASIC_CONVERSION)
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82 summary = r.summary(pc, loadings="TRUE")
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83 ncomps = len(summary['sdev'])
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84
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85 if type(summary['sdev']) == type({}):
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86 comps_unsorted = summary['sdev'].keys()
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87 comps=[]
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88 sd = summary['sdev'].values()
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89 for i in range(ncomps):
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90 sd[i] = summary['sdev'].values()[comps_unsorted.index('Comp.%s' %(i+1))]
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91 comps.append('Comp.%s' %(i+1))
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92 elif type(summary['sdev']) == type([]):
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93 comps=[]
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94 for i in range(ncomps):
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95 comps.append('Comp.%s' %(i+1))
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96 sd = summary['sdev']
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97
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98 print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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99 print >>fout, "#Std. deviation\t%s" %("\t".join(["%.4g" % el for el in sd]))
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100 total_var = 0
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101 vars = []
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102 for s in sd:
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103 var = s*s
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104 total_var += var
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105 vars.append(var)
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106 for i,var in enumerate(vars):
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107 vars[i] = vars[i]/total_var
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108
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109 print >>fout, "#Proportion of variance explained\t%s" %("\t".join(["%.4g" % el for el in vars]))
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110
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111 print >>fout, "#Loadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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112 xcolnames = ["c%d" %(el+1) for el in x_cols]
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113 if 'loadings' in summary: #in case of princomp
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114 loadings = 'loadings'
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115 elif 'rotation' in summary: #in case of prcomp
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116 loadings = 'rotation'
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117 for i,val in enumerate(summary[loadings]):
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118 print >>fout, "%s\t%s" %(xcolnames[i], "\t".join(["%.4g" % el for el in val]))
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119
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120 print >>fout, "#Scores\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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121 if 'scores' in summary: #in case of princomp
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122 scores = 'scores'
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123 elif 'x' in summary: #in case of prcomp
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124 scores = 'x'
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125 for obs,sc in enumerate(summary[scores]):
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126 print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in sc]))
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127
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128 r.pdf( outfile2, 8, 8 )
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129 r.biplot(pc)
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130 r.dev_off()