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1 #!/usr/bin/env python
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2
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3 ######################################################################
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4 # Copyright (c) 2016 Northrop Grumman.
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5 # All rights reserved.
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6 ######################################################################
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7 from __future__ import print_function
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8 import sys
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9 import os
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10 from argparse import ArgumentParser
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11 from jinja2 import Environment, FileSystemLoader
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12
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13 profile_key = {
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14 "1": "-",
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15 "2": "lo",
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16 "3": "+",
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17 "4": "hi"
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18 }
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19
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20
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21 def run_flowCL(phenotype, output_txt, output_pdf, tool):
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22 run_command = " ". join(["Rscript --slave --vanilla", tool, "--args", output_txt, phenotype])
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23 os.system(run_command)
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24 get_graph = " ".join(["mv flowCL_results/*.pdf", output_pdf])
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25 os.system(get_graph)
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26 return
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27
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28
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29 def generate_flowCL_query(list_markers, list_types):
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30 if (len(list_markers) != len(list_types)):
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31 return("pb with headers")
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32 query = []
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33 # go through both lists, remove fsc/ssc
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34 for i in range(1, len(list_markers)):
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35 if not list_markers[i].startswith("FSC") and not list_markers[i].startswith("SSC"):
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36 query.append(list_markers[i].upper())
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37 query.append(profile_key[list_types[i]])
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38 # return concatenated string
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39 return("".join(query))
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40
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41
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42 def translate_profiles(input_file, tool_dir, output, html_dir):
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43 os.mkdir(html_dir)
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44
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45 tool = "/".join([tool_dir, "getOntology.R"])
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46 html_table = "".join([html_dir, "/CLprofiles.txt"])
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47 score_table = "".join(["cp ", input_file, " ", html_dir, "/scores.txt"])
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48 os.system(score_table)
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49
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50 # read profile
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51 with open(input_file, "r") as flock_profiles, open(html_table, "w") as out:
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52 headers = flock_profiles.readline()
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53 headers = headers.strip()
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54 # get all headers except for last 2 (count + percentage)
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55 markers = headers.split("\t")[:-2]
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56 counter = 0
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57
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58 out.write("Population\tFlowCL Query\tNb Results\tLink to PDF\t")
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59 out.write("Top Result Label\tTop Result Score\tTop Result CL\n")
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60 queries = {}
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61 # create marker query for each population
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62 for lines in flock_profiles:
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63 lines = lines.strip("\n")
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64 pop_profile = lines.split("\t")[:-2]
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65 flowcl_query = generate_flowCL_query(markers, pop_profile)
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66 counter += 1
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67 nb_results = "0"
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68 top_label = "no_match"
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69 top_score = "NA"
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70 top_CL = "NA"
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71 pdf_link = "NA"
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72 # check if query was run before
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73 if flowcl_query not in queries:
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74 # create filenames for results & graphs
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75 txt = "".join(["flowcl_pop", str(counter).zfill(2), ".txt"])
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76 text_result = "/".join([html_dir, txt])
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77 graph = "".join(["flowcl_pop", str(counter).zfill(2), ".pdf"])
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78 graph_output = "/".join([html_dir, graph])
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79 # run flowCL for each marker profile
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80 run_flowCL(flowcl_query, text_result, graph_output, tool)
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81
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82 # test that text file exists if not results are all NAs:
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83 if os.path.isfile(text_result):
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84 with open(text_result, "r") as res:
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85 for line in res:
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86 if line.startswith("Score"):
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87 data = line.split(") ")
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88 top_score = data[2][:-2]
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89 tot_results = len(data) - 2
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90 nb_results = str(tot_results)
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91 if tot_results == 5:
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92 if len(data[6].split("+")) > 1:
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93 nb_results = "5+"
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94 elif line.startswith("Cell ID"):
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95 prep_link = line.split(") ")[1][:-2]
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96 cl = prep_link.replace("_", ":")
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97 link = "".join(['<a href="http://www.immport-labs.org/immport-ontology/public/home/home/', cl, '" target="_blank">'])
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98 top_CL = "".join([link, prep_link, "</a>"])
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99 elif line.startswith("Cell Label"):
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100 top_label = line.split(") ")[1][:-2]
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101 pdf_link = "".join(['<a href="', graph, '" target="_blank">PDF</a>'])
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102 tmpflowcl_query = "".join(['<a href="', txt, '" target="_blank">', flowcl_query, '</a>'])
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103
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104 queries[flowcl_query] = {
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105 "query": tmpflowcl_query,
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106 "results": nb_results,
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107 "pdf": pdf_link,
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108 "label": top_label,
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109 "score": top_score,
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110 "CL": top_CL
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111 }
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112 # write query results to CLprofiles.txt
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113 out.write("\t".join([pop_profile[0],
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114 queries[flowcl_query]["query"],
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115 queries[flowcl_query]["results"],
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116 queries[flowcl_query]["pdf"],
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117 queries[flowcl_query]["label"],
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118 queries[flowcl_query]["score"],
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119 queries[flowcl_query]["CL"]]) + "\n")
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120
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121 env = Environment(loader=FileSystemLoader(tool_dir + "/templates"))
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122 template = env.get_template("profileCLs.template")
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123
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124 real_directory = html_dir.replace("/job_working_directory", "")
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125 context = {'outputDirectory': real_directory}
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126 overview = template.render(**context)
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127 with open(output, "w") as outf:
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128 outf.write(overview)
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129
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130
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131 if __name__ == "__main__":
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132 parser = ArgumentParser(
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133 prog="getCLs_from_profile",
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134 description="runs flowCL on a each population defined by FLOCK.")
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135
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136 parser.add_argument(
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137 '-i',
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138 dest="input_file",
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139 required=True,
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140 help="File location for the profile.txt from FLOCK.")
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141
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142 parser.add_argument(
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143 '-o',
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144 dest="output",
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145 required=True,
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146 help="Name of the output html file.")
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147
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148 parser.add_argument(
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149 '-d',
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150 dest="html_dir",
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151 required=True,
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152 help="Path to html supporting directory.")
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153
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154 parser.add_argument(
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155 '-t',
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156 dest="tool_dir",
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157 required=True,
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158 help="Path to the tool directory")
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159
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160 args = parser.parse_args()
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161
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162 translate_profiles(args.input_file, args.tool_dir, args.output, args.html_dir)
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163 sys.exit(0)
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