Mercurial > repos > proteore > proteore_venn_diagram

annotate venn_diagram.py @ 8:bca31ac678f1 draft

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author proteore
date Fri, 28 Jun 2019 05:18:44 -0400
parents d1fd04dcb13a
children e744a43171ff
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1 #!/usr/bin/env python2.7
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2
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3 import os
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4 import sys
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5 import json
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6 import operator
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7 import argparse
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8 import re, csv
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9 from itertools import combinations
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10
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11 CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
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12
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13 ##################################################################################################################################################
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14 # FUNCTIONS
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15 ##################################################################################################################################################
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16
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17 def isnumber(format, n):
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18 """
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19 Check if an element is integer or float
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20 """
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21 float_format = re.compile(r"^[-]?[1-9][0-9]*.?[0-9]+$")
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22 int_format = re.compile(r"^[-]?[1-9][0-9]*$")
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23 test = ""
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24 if format == "int":
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25 test = re.match(int_format, n)
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26 elif format == "float":
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27 test = re.match(float_format, n)
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28 if test:
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29 return True
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30 else:
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31 return False
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32
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33 def input_to_dict(inputs):
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34 """
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35 Parse input and return a dictionary of name and data of each lists/files
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36 """
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37 comp_dict = {}
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38 title_dict = {}
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39 c = ["A", "B", "C", "D", "E", "F"]
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40 for i in range(len(inputs)):
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41 input_file = inputs[i][0]
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42 name = inputs[i][1]
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43 input_type = inputs[i][2]
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44 title = c[i]
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45 title_dict[title] = name
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46 ids = set()
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47 if input_type == "file":
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48 header = inputs[i][3]
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49 ncol = inputs[i][4]
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50 with open(input_file,"r") as handle :
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51 file_content = csv.reader(handle,delimiter="\t")
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52 file_content = list(file_content) #csv object to list
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53
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54 # Check if column number is in right form
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55 if isnumber("int", ncol.replace("c", "")):
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56 if header == "true":
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57 file_content = [x for x in [line[int(ncol.replace("c", ""))-1].split(";") for line in file_content[1:]]] # gets ids from defined column
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58 else:
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59 file_content = [x for x in [line[int(ncol.replace("c", ""))-1].split(";") for line in file_content]]
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60 else:
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61 raise ValueError("Please fill in the right format of column number")
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62 else:
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63 ids = set()
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64 file_content = inputs[i][0].split()
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65 file_content = [x.split(";") for x in file_content]
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66
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67 file_content = [item.strip() for sublist in file_content for item in sublist if item != ''] #flat list of list of lists, remove empty items
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68 ids.update(file_content)
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69 if 'NA' in ids : ids.remove('NA')
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70 comp_dict[title] = ids
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71
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72 return comp_dict, title_dict
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73
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74 def intersect(comp_dict):
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75 """
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76 Calculate the intersections of input
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77 """
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78 names = set(comp_dict)
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79 for i in range(1, len(comp_dict) + 1):
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80 for group in combinations(sorted(comp_dict), i):
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81 others = set()
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82 [others.add(name) for name in names if name not in group]
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83 difference = []
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84 intersected = set.intersection(*(comp_dict[k] for k in group))
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85 if len(others) > 0:
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86 difference = intersected.difference(set.union(*(comp_dict[k] for k in others)))
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87 yield group, list(intersected), list(difference)
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88
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89 def diagram(comp_dict, title_dict):
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90 """
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91 Create json string for jvenn diagram plot
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92 """
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93 result = {}
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94 result["name"] = {}
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95 for k in comp_dict.keys():
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96 result["name"][k] = title_dict[k]
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97
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98 result["data"] = {}
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99 result["values"] = {}
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100 for group, intersected, difference in intersect(comp_dict):
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101 if len(group) == 1:
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102 result["data"]["".join(group)] = difference
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103 result["values"]["".join(group)] = len(difference)
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104 elif len(group) > 1 and len(group) < len(comp_dict):
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105 result["data"]["".join(group)] = difference
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106 result["values"]["".join(group)] = len(difference)
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107 elif len(group) == len(comp_dict):
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108 result["data"]["".join(group)] = intersected
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109 result["values"]["".join(group)] = len(intersected)
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110
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111 return result
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112
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113 #Write intersections of input to text output file
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114 def write_text_venn(json_result):
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115 lines = []
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116 result = dict((k, v) for k, v in json_result["data"].iteritems() if v != [])
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117 for key in result :
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118 if 'NA' in result[key] : result[key].remove("NA")
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119 list_names = dict((k, v) for k, v in json_result["name"].iteritems() if v != [])
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120 nb_lines_max = max(len(v) for v in result.values())
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121
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122 #get list names associated to each column
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123 column_dict = {}
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124 for key in result :
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125 if key in list_names :
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126 column_dict[key] = list_names[key]
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127 else :
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128 keys= list(key)
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129 column_dict[key] = "_".join([list_names[k] for k in keys])
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130
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131 #construct tsv
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132 for key in result :
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133 line = [column_dict[key]]
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134 line.extend(result[key])
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135 if len(line) < nb_lines_max :
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136 line.extend(['NA']*(nb_lines_max-len(line)))
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137 lines.append(line)
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138 #transpose tsv
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139 lines=zip(*lines)
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140
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141 with open("venn_diagram_text_output.tsv", "w") as output:
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142 tsv_output = csv.writer(output, delimiter='\t')
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143 tsv_output.writerows(lines)
0
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144
3
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145 def write_summary(summary_file, inputs):
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146 """
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147 Paste json string into template file
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148 """
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149 a, b = input_to_dict(inputs)
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150 data = diagram(a, b)
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151 write_text_venn(data)
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152
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153 to_replace = {
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154 "series": [data],
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155 "displayStat": "true",
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156 "displaySwitch": "true",
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157 "shortNumber": "true",
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158 }
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159
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160 FH_summary_tpl = open(os.path.join(CURRENT_DIR, "jvenn_template.html"))
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161 FH_summary_out = open(summary_file, "w" )
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162 for line in FH_summary_tpl:
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163 if "###JVENN_DATA###" in line:
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164 line = line.replace("###JVENN_DATA###", json.dumps(to_replace))
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165 FH_summary_out.write(line)
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166
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167 FH_summary_out.close()
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168 FH_summary_tpl.close()
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169
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170 def process(args):
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171 write_summary(args.summary, args.input)
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172
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173
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174 ##################################################################################################################################################
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175 # MAIN
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176 ##################################################################################################################################################
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177 if __name__ == '__main__':
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178 # Parse parameters
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179 parser = argparse.ArgumentParser(description='Filters an abundance file')
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180 group_input = parser.add_argument_group( 'Inputs' )
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181 group_input.add_argument('--input', nargs="+", action="append", required=True, help="The input tabular file.")
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182 group_output = parser.add_argument_group( 'Outputs' )
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183 group_output.add_argument('--summary', default="summary.html", help="The HTML file containing the graphs. [Default: %(default)s]")
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184 args = parser.parse_args()
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185
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186 # Process
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187 process( args )