annotate tools/taxonomy/poisson2test.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/local/bin/python
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2
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3 import sys
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4 from math import *
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5 from rpy import *
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6
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7
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8 if ((len(sys.argv)-1) != 6):
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9 print 'too few parameters'
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10 print 'usage: inputfile, col1, col2, d-value(not 0), p-val correction method(0 or 1)'
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11 sys.exit()
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12
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13 try:
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14 lines_arr = open(sys.argv[1]).readlines()
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15 except IOError:
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16 print'cannot open',sys.argv[1]
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17 sys.exit()
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18
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19 try:
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20 i = int(sys.argv[2]) #first column to compare
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21 j = int(sys.argv[3]) #second colum to compare
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22 d = float(sys.argv[4]) #correction factor
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23 k = int(sys.argv[5]) #p-val correction method
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24 outfile = open(sys.argv[6],'w') # output data
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25
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26 if (i>j):
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27 print 'column order not correct col1 < col2'
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28 print 'usage: inputfile, col1, col2, d-value, p-val correction method'
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29 sys.exit()
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30
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31 try:
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32 a = 1 / d
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33 assert k in [0,1]
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34 except ZeroDivisionError:
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35 print 'd cannot be 0'
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36 print 'usage: inputfile, col1, col2, d-value, p-val correction method'
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37 sys.exit()
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38 except:
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39 print ' p-val correction should be 0 or 1 (0 = "bonferroni", 1 = "fdr")'
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40 print 'usage: inputfile, col1, col2, d-value, p-val correction method'
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41 sys.exit()
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42 except ValueError:
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43 print 'parameters are not integers'
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44 print 'usage: inputfile, col1, col2, d-value, p-val correction method'
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45 sys.exit()
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46
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47
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48 fsize = len(lines_arr)
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49
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50 z1 = []
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51 z2 = []
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52 pz1 = []
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53 pz2 = []
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54 field = []
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55
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56 if d<1: # Z score calculation
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57 for line in lines_arr:
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58 line.strip()
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59 field = line.split('\t')
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60
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61 x = int(field[j-1]) #input column 2
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62 y = int(field[i-1]) #input column 1
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63 if y>x:
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64 z1.append(float((y - ((1/d)*x))/sqrt((1/d)*(x + y))))
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65 z2.append(float((2*(sqrt(y+(3/8))-sqrt((1/d)*(x+(3/8)))))/sqrt(1+(1/d))))
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66 else:
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67 tmp_var1 = x
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68 x = y
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69 y = tmp_var1
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70 z1.append(float((y - (d*x))/sqrt(d*(x + y))))
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71 z2.append(float((2*(sqrt(y+(3/8))-sqrt(d*(x+(3/8)))))/sqrt(1+d)))
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72
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73 else: #d>1 Z score calculation
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74 for line in lines_arr:
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75 line.strip()
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76 field = line.split('\t')
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77 x = int(field[i-1]) #input column 1
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78 y = int(field[j-1]) #input column 2
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79
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80 if y>x:
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81 z1.append(float((y - (d*x))/sqrt(d*(x + y))))
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82 z2.append(float((2*(sqrt(y+(3/8))-sqrt(d*(x+(3/8)))))/sqrt(1+d)))
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83 else:
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84 tmp_var2 = x
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85 x = y
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86 y = tmp_var2
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87 z1.append(float((y - ((1/d)*x))/sqrt((1/d)*(x + y))))
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88 z2.append(float((2*(sqrt(y+(3/8))-sqrt((1/d)*(x+(3/8)))))/sqrt(1+(1/d))))
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89
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90
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91
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92
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93
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94 # P-value caluculation for z1 and z2
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95 for p in z1:
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96
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97 pz1.append(float(r.pnorm(-abs(float(p)))))
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98
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99 for q in z2:
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100
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101 pz2.append(float(r.pnorm(-abs(float(q)))))
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102
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103 # P-value correction for pz1 and pz2
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104
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105 if k == 0:
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106 corrz1 = r.p_adjust(pz1,"bonferroni",fsize)
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107 corrz2 = r.p_adjust(pz2,"bonferroni",fsize)
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108
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109
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110 else:
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111
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112 corrz1 = r.p_adjust(pz1,"fdr",fsize)
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113 corrz2 = r.p_adjust(pz2,"fdr",fsize)
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114
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115
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116 #printing all columns
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117 for n in range(fsize):
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118 print >> outfile, "%s\t%4.3f\t%4.3f\t%8.6f\t%8.6f\t%8.6f\t%8.6f" %(lines_arr[n].strip(),z1[n],z2[n],pz1[n],pz2[n],corrz1[n],corrz2[n])
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119
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