1 | #!/usr/bin/env python |
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2 | |
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3 | """ |
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4 | This tool takes the following file pairs as input: |
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5 | a) input_snp : A file with identifiers for SNPs (one on each line) |
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6 | b) ldfile : A file where each line has the following |
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7 | snp list |
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8 | where "snp" is an identifier for one SNP and the "list" is a |
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9 | comma separated list of all the other snps that are in LD with |
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10 | it (as per some threshold of rsquare) |
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11 | |
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12 | The output is a set of tag SNPs for the given datasets |
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13 | |
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14 | The algorithm is as follows: |
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15 | |
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16 | a) Construct a graph for each population, where each node is a SNP and two nodes |
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17 | are connected using an edge iff they are in LD. |
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18 | b) For each SNP, count the total number of connected nodes, which have not yet |
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19 | been visited. |
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20 | c) Find the SNP with the highest count and assign it to be a tag SNP. |
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21 | d) Mark that SNP and all the snps connected to it as "visited". This should be |
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22 | done for each population. |
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23 | e) Continue steps b-e until all SNPs, in all populations have been visited. |
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24 | """ |
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25 | |
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26 | from sys import argv, stderr, exit |
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27 | from getopt import getopt, GetoptError |
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28 | |
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29 | import os |
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30 | import heapq |
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31 | |
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32 | __author__ = "Aakrosh Ratan" |
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33 | __email__ = "ratan@bx.psu.edu" |
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34 | |
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35 | # do we want the debug information to be printed? |
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36 | debug_flag = False |
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37 | |
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38 | class node: |
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39 | def __init__(self, name): |
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40 | self.name = name |
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41 | self.edges = [] |
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42 | self.visited = False |
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43 | |
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44 | # return the number of nodes connected to this node, that have yet to be |
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45 | # visited |
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46 | def num_not_visited(self): |
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47 | num = 0 |
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48 | for n in self.edges: |
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49 | if n.visited == False: num += 1 |
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50 | return num |
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51 | |
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52 | def __cmp__(self, other): |
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53 | return other.num_not_visited() - self.num_not_visited() |
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54 | |
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55 | def __str__(self): |
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56 | return self.name |
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57 | |
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58 | class graph: |
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59 | def __init__(self): |
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60 | self.nodes = {} |
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61 | |
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62 | def __str__(self): |
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63 | string = "" |
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64 | for n1 in self.nodes.values(): |
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65 | n2s = [x.name for x in n1.edges] |
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66 | string += "%s %s\n" % (n1.name, ",".join(n2s)) |
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67 | return string[:-1] |
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68 | |
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69 | def add_node(self, n): |
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70 | self.nodes[n.name] = n |
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71 | |
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72 | def add_edges(self, n1, n2): |
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73 | assert n1.name in self.nodes |
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74 | assert n2.name in self.nodes |
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75 | n1.edges.append(n2) |
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76 | n2.edges.append(n1) |
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77 | |
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78 | def check_graph(self): |
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79 | for n in self.nodes.values(): |
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80 | ms = [x for x in n.edges] |
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81 | for m in ms: |
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82 | if n not in m.edges: |
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83 | print >> stderr, "check : %s - %s" % (n,m) |
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84 | |
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85 | def construct_graph(ldfile, snpfile): |
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86 | # construct the initial graph. add all the SNPs as nodes |
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87 | g = graph() |
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88 | file = open(snpfile, "r") |
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89 | |
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90 | for line in file: |
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91 | # ignore empty lines and add the remainder to the graph |
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92 | if len(line.strip()) == 0: continue |
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93 | n = node(line.strip()) |
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94 | g.add_node(n) |
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95 | |
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96 | file.close() |
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97 | print >> stderr, "Added %d nodes to a graph" % len(g.nodes) |
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98 | |
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99 | # now add all the edges |
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100 | file = open(ldfile, "r") |
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101 | |
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102 | for line in file: |
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103 | tokens = line.split() |
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104 | assert len(tokens) == 2 |
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105 | |
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106 | # if this node is in the graph, then we need to construct an edge from |
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107 | # this node to all the nodes which are highly related to it |
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108 | if tokens[0] in g.nodes: |
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109 | n1 = g.nodes[tokens[0]] |
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110 | n2s = [g.nodes[x] for x in tokens[1].split(",")] |
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111 | |
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112 | for n2 in n2s: |
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113 | g.add_edges(n1, n2) |
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114 | |
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115 | file.close() |
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116 | print >> stderr, "Added all edges to the graph" |
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117 | |
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118 | return g |
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119 | |
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120 | def check_output(g, tagsnps): |
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121 | # find all the nodes in the graph |
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122 | allsnps = [x.name for x in g.nodes.values()] |
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123 | |
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124 | # find the nodes that are covered by our tagsnps |
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125 | mysnps = [x.name for x in tagsnps] |
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126 | |
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127 | for n in tagsnps: |
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128 | for m in n.edges: |
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129 | mysnps.append(m.name) |
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130 | |
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131 | mysnps = list(set(mysnps)) |
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132 | |
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133 | if set(allsnps) != set(mysnps): |
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134 | diff = list(set(allsnps) - set(mysnps)) |
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135 | print >> stderr, "%s are not covered" % ",".join(diff) |
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136 | |
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137 | def main(ldfile, snpsfile, required, excluded): |
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138 | # construct the graph |
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139 | g = construct_graph(ldfile, snpsfile) |
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140 | if debug_flag == True: g.check_graph() |
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141 | |
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142 | tagsnps = [] |
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143 | neighbors = {} |
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144 | |
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145 | # take care of the SNPs that are required to be TagSNPs |
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146 | for s in required: |
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147 | t = g.nodes[s] |
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148 | |
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149 | t.visited = True |
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150 | ns = [] |
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151 | |
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152 | for n in t.edges: |
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153 | if n.visited == False: ns.append(n.name) |
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154 | n.visited = True |
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155 | |
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156 | tagsnps.append(t) |
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157 | neighbors[t.name] = list(set(ns)) |
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158 | |
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159 | # find the tag SNPs for this graph |
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160 | data = [x for x in g.nodes.values()] |
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161 | heapq.heapify(data) |
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162 | |
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163 | while data: |
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164 | s = heapq.heappop(data) |
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165 | |
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166 | if s.visited == True or s.name in excluded: continue |
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167 | |
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168 | s.visited = True |
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169 | ns = [] |
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170 | |
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171 | for n in s.edges: |
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172 | if n.visited == False: ns.append(n.name) |
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173 | n.visited = True |
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174 | |
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175 | tagsnps.append(s) |
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176 | neighbors[s.name] = list(set(ns)) |
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177 | |
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178 | heapq.heapify(data) |
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179 | |
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180 | for s in tagsnps: |
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181 | if len(neighbors[s.name]) > 0: |
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182 | print "%s\t%s" % (s, ",".join(neighbors[s.name])) |
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183 | continue |
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184 | print s |
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185 | |
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186 | if debug_flag == True: check_output(g, tagsnps) |
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187 | |
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188 | def read_list(filename): |
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189 | assert os.path.exists(filename) == True |
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190 | file = open(filename, "r") |
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191 | list = {} |
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192 | |
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193 | for line in file: |
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194 | list[line.strip()] = 1 |
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195 | |
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196 | file.close() |
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197 | return list |
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198 | |
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199 | def usage(): |
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200 | f = stderr |
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201 | print >> f, "usage:" |
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202 | print >> f, "senatag [options] neighborhood.txt inputsnps.txt" |
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203 | print >> f, "where inputsnps.txt is a file of snps from one population" |
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204 | print >> f, "where neighborhood.txt is neighborhood details for the pop." |
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205 | print >> f, "where the options are:" |
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206 | print >> f, "-h,--help : print usage and quit" |
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207 | print >> f, "-d,--debug: print debug information" |
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208 | print >> f, "-e,--excluded : file with names of SNPs that cannot be TagSNPs" |
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209 | print >> f, "-r,--required : file with names of SNPs that should be TagSNPs" |
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210 | |
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211 | if __name__ == "__main__": |
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212 | try: |
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213 | opts, args = getopt(argv[1:], "hdr:e:",\ |
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214 | ["help", "debug", "required=", "excluded="]) |
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215 | except GetoptError, err: |
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216 | print str(err) |
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217 | usage() |
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218 | exit(2) |
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219 | |
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220 | required = {} |
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221 | excluded = {} |
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222 | |
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223 | for o, a in opts: |
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224 | if o in ("-h", "--help"): |
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225 | usage() |
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226 | exit() |
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227 | elif o in ("-d", "--debug"): |
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228 | debug_flag = True |
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229 | elif o in ("-r", "--required"): |
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230 | required = read_list(a) |
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231 | elif o in ("-e", "--excluded"): |
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232 | excluded = read_list(a) |
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233 | else: |
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234 | assert False, "unhandled option" |
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235 | |
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236 | if len(args) != 2: |
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237 | usage() |
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238 | exit(3) |
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239 | |
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240 | assert os.path.exists(args[0]) == True |
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241 | assert os.path.exists(args[1]) == True |
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242 | |
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243 | main(args[0], args[1], required, excluded) |
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