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1 #!/home/jjjjia/.conda/envs/py36/bin/python
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2
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3 #$ -S /home/jjjjia/.conda/envs/py36/bin/python
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4 #$ -V # Pass environment variables to the job
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5 #$ -N CPO_pipeline # Replace with a more specific job name
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6 #$ -wd /home/jjjjia/testCases # Use the current working dir
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7
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7 #$ -pe smp 1 # Parallel Environment (how many cores)
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1
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8 #$ -l h_vmem=11G # Memory (RAM) allocation *per core*
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9 #$ -e ./logs/$JOB_ID.err
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10 #$ -o ./logs/$JOB_ID.log
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11 #$ -m ea
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12 #$ -M bja20@sfu.ca
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13
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7
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14 # >python cpo_galaxy_tree.py -t /path/to/tree.ph -d /path/to/distance/matrix -m /path/to/metadata
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15
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16 # <requirements>
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17 # <requirement type="package" version="0.23.4">pandas</requirement>
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18 # <requirement type="package" version="3.6">python</requirement>
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19 # <requirement type="package" version="3.1.1">ete3</requirement>
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20 # <requirement type="package" version="5.6.0">pyqt</requirement>
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21 # </requirements>
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22
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23 import subprocess
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24 import pandas #conda pandas
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25 import optparse
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26 import os
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27 os.environ['QT_QPA_PLATFORM']='offscreen'
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28 import datetime
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29 import sys
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30 import time
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31 import urllib.request
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32 import gzip
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33 import collections
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34 import json
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35 import numpy #conda numpy
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36 import ete3 as e #conda ete3 3.1.1**** >requires pyqt5
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6
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37
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38
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39 #parses some parameters
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40 parser = optparse.OptionParser("Usage: %prog [options] arg1 arg2 ...")
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41 parser.add_option("-t", "--tree", dest="treePath", type="string", default="./pipelineTest/tree.txt", help="identifier of the isolate")
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42 parser.add_option("-d", "--distance", dest="distancePath", type="string", default="./pipelineTest/distance.tab", help="absolute file path forward read (R1)")
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43 parser.add_option("-m", "--metadata", dest="metadataPath", type="string", default="./pipelineTest/metadata.tsv",help="absolute file path to reverse read (R2)")
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44 (options,args) = parser.parse_args()
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45 treePath = str(options.treePath).lstrip().rstrip()
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46 distancePath = str(options.distancePath).lstrip().rstrip()
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47 metadataPath = str(options.metadataPath).lstrip().rstrip()
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48
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49
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50 #region result objects
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51 #define some objects to store values from results
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52 #//TODO this is not the proper way of get/set private object variables. every value has manually assigned defaults intead of specified in init(). Also, use property(def getVar, def setVar).
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53 class workflowResult(object):
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54 def __init__(self):
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55 self.new = False
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56 self.ID = ""
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57 self.ExpectedSpecies = ""
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58 self.MLSTSpecies = ""
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59 self.SequenceType = ""
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60 self.MLSTScheme = ""
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61 self.CarbapenemResistanceGenes =""
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62 self.OtherAMRGenes=""
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63 self.TotalPlasmids = 0
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64 self.plasmids = []
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65 self.DefinitelyPlasmidContigs =""
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66 self.LikelyPlasmidContigs=""
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67 self.row = ""
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68 class plasmidObj(object):
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69 def __init__(self):
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70 self.PlasmidsID = 0
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71 self.Num_Contigs = 0
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72 self.PlasmidLength = 0
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73 self.PlasmidRepType = ""
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74 self.PlasmidMobility = ""
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75 self.NearestReference = ""
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76
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77 #endregion
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78
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79 #region useful functions
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80 def read(path): #read in a text file to a list
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81 return [line.rstrip('\n') for line in open(path)]
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82 def execute(command): #subprocess.popen call bash command
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83 process = subprocess.Popen(command, shell=False, cwd=curDir, universal_newlines=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
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84
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85 # Poll process for new output until finished
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86 while True:
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87 nextline = process.stdout.readline()
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88 if nextline == '' and process.poll() is not None:
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89 break
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90 sys.stdout.write(nextline)
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91 sys.stdout.flush()
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92
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93 output = process.communicate()[0]
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94 exitCode = process.returncode
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95
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96 if (exitCode == 0):
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97 return output
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98 else:
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99 raise subprocess.CalledProcessError(exitCode, command)
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100 def httpGetFile(url, filepath=""): #download a file from the web
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101 if (filepath == ""):
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102 return urllib.request.urlretrieve(url)
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103 else:
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104 urllib.request.urlretrieve(url, filepath)
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105 return True
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106 def gunzip(inputpath="", outputpath=""): #gunzip
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107 if (outputpath == ""):
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108 with gzip.open(inputpath, 'rb') as f:
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109 gzContent = f.read()
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110 return gzContent
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111 else:
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112 with gzip.open(inputpath, 'rb') as f:
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113 gzContent = f.read()
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114 with open(outputpath, 'wb') as out:
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115 out.write(gzContent)
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116 return True
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117 def addFace(name): #function to add a facet to a tree
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118 #if its the reference branch, populate the faces with column headers
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119 face = e.faces.TextFace(name,fsize=10,tight_text=True)
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120 face.border.margin = 5
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121 face.margin_right = 5
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122 face.margin_left = 5
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123 return face
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124 #endregion
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125
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126 #region functions to parse result files
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127 def ParseWorkflowResults(pathToResult):
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128 _worflowResult = {}
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129 r = pandas.read_csv(pathToResult, delimiter='\t', header=0)
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130 r = r.replace(numpy.nan, '', regex=True)
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131 for i in range(len(r.index)):
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132 _results = workflowResult()
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133 if(str(r.loc[r.index[i], 'new']).lower() == "new"):
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134 _results.new = True
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135 else:
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136 _results.new = False
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137 _results.ID = str(r.loc[r.index[i], 'ID'])
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138 _results.ExpectedSpecies = str(r.loc[r.index[i], 'Expected Species'])
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139 _results.MLSTSpecies = str(r.loc[r.index[i], 'MLST Species'])
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140 _results.SequenceType = str(r.loc[r.index[i], 'Sequence Type'])
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141 _results.MLSTScheme = (str(r.loc[r.index[i], 'MLST Scheme']))
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142 _results.CarbapenemResistanceGenes = (str(r.loc[r.index[i], 'Carbapenem Resistance Genes']))
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143 _results.OtherAMRGenes = (str(r.loc[r.index[i], 'Other AMR Genes']))
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144 _results.TotalPlasmids = int(r.loc[r.index[i], 'Total Plasmids'])
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145 for j in range(0,_results.TotalPlasmids):
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146 _plasmid = plasmidObj()
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147 _plasmid.PlasmidsID =(((str(r.loc[r.index[i], 'Plasmids ID'])).split(";"))[j])
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148 _plasmid.Num_Contigs = (((str(r.loc[r.index[i], 'Num_Contigs'])).split(";"))[j])
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149 _plasmid.PlasmidLength = (((str(r.loc[r.index[i], 'Plasmid Length'])).split(";"))[j])
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150 _plasmid.PlasmidRepType = (((str(r.loc[r.index[i], 'Plasmid RepType'])).split(";"))[j])
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151 _plasmid.PlasmidMobility = ((str(r.loc[r.index[i], 'Plasmid Mobility'])).split(";"))[j]
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152 _plasmid.NearestReference = ((str(r.loc[r.index[i], 'Nearest Reference'])).split(";"))[j]
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153 _results.plasmids.append(_plasmid)
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154 _results.DefinitelyPlasmidContigs = (str(r.loc[r.index[i], 'Definitely Plasmid Contigs']))
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155 _results.LikelyPlasmidContigs = (str(r.loc[r.index[i], 'Likely Plasmid Contigs']))
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156 _results.row = "\t".join(str(x) for x in r.ix[i].tolist())
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157 _worflowResult[_results.ID] = _results
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158 return _worflowResult
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159
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160 #endregion
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161
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162 def Main():
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163 metadata = ParseWorkflowResults(metadataPath)
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164 distance = read(distancePath)
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165 treeFile = "".join(read(treePath))
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166
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167 distanceDict = {} #store the distance matrix as rowname:list<string>
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168 for i in range(len(distance)):
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169 temp = distance[i].split("\t")
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170 distanceDict[temp[0]] = temp[1:]
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171
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172 #region create box tree
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173 #region step5: tree construction
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174 treeFile = "".join(read(treePath))
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175 t = e.Tree(treeFile)
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176 t.set_outgroup(t&"Reference")
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177
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178 #set the tree style
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179 ts = e.TreeStyle()
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180 ts.show_leaf_name = False
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181 ts.show_branch_length = True
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182 ts.scale = 2000 #pixel per branch length unit
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183 ts.branch_vertical_margin = 15 #pixel between branches
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184 style2 = e.NodeStyle()
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185 style2["fgcolor"] = "#000000"
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186 style2["shape"] = "circle"
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187 style2["vt_line_color"] = "#0000aa"
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188 style2["hz_line_color"] = "#0000aa"
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189 style2["vt_line_width"] = 2
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190 style2["hz_line_width"] = 2
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191 style2["vt_line_type"] = 0 # 0 solid, 1 dashed, 2 dotted
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192 style2["hz_line_type"] = 0
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193 for n in t.traverse():
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194 n.set_style(style2)
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195
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196 #find the plasmid origins
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197 plasmidIncs = {}
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198 for key in metadata:
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199 for plasmid in metadata[key].plasmids:
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200 for inc in plasmid.PlasmidRepType.split(","):
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201 if (inc.lower().find("inc") > -1):
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202 if not (inc in plasmidIncs):
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203 plasmidIncs[inc] = [metadata[key].ID]
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204 else:
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205 if metadata[key].ID not in plasmidIncs[inc]:
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206 plasmidIncs[inc].append(metadata[key].ID)
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207 #plasmidIncs = sorted(plasmidIncs)
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208 for n in t.traverse(): #loop through the nodes of a tree
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209 if (n.is_leaf() and n.name == "Reference"):
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210 #if its the reference branch, populate the faces with column headers
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211 index = 0
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212 (t&"Reference").add_face(addFace("SampleID"), index, "aligned")
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213 index = index + 1
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214 (t&"Reference").add_face(addFace("New?"), index, "aligned")
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215 index = index + 1
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216 for i in range(len(plasmidIncs)): #this loop adds the columns (aka the incs) to the reference node
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217 (t&"Reference").add_face(addFace(list(plasmidIncs.keys())[i]), i + index, "aligned")
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218 index = index + len(plasmidIncs)
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219 (t&"Reference").add_face(addFace("MLSTScheme"), index, "aligned")
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220 index = index + 1
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221 (t&"Reference").add_face(addFace("Sequence Type"), index, "aligned")
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222 index = index + 1
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223 (t&"Reference").add_face(addFace("Carbapenamases"), index, "aligned")
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224 index = index + 1
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225 for i in range(len(distanceDict[list(distanceDict.keys())[0]])): #this loop adds the distance matrix
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226 (t&"Reference").add_face(addFace(distanceDict[list(distanceDict.keys())[0]][i]), index + i, "aligned")
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227 index = index + len(distanceDict[list(distanceDict.keys())[0]])
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228 elif (n.is_leaf() and not n.name == "Reference"):
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229 #not reference branches, populate with metadata
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230 index = 0
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231 mData = metadata[n.name.replace(".fa","")]
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232 n.add_face(addFace(mData.ID), index, "aligned")
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233 index = index + 1
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234 if (metadata[n.name.replace(".fa","")].new == True): #new column
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235 face = e.RectFace(30,30,"green","green") # TextFace("Y",fsize=10,tight_text=True)
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236 face.border.margin = 5
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237 face.margin_right = 5
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238 face.margin_left = 5
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239 face.vt_align = 1
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240 face.ht_align = 1
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241 n.add_face(face, index, "aligned")
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242 index = index + 1
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243 for incs in plasmidIncs: #this loop adds presence/absence to the sample nodes
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244 if (n.name.replace(".fa","") in plasmidIncs[incs]):
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245 face = e.RectFace(30,30,"black","black") # TextFace("Y",fsize=10,tight_text=True)
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246 face.border.margin = 5
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247 face.margin_right = 5
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248 face.margin_left = 5
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249 face.vt_align = 1
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250 face.ht_align = 1
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251 n.add_face(face, list(plasmidIncs.keys()).index(incs) + index, "aligned")
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252 index = index + len(plasmidIncs)
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253 n.add_face(addFace(mData.MLSTSpecies), index, "aligned")
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254 index = index + 1
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255 n.add_face(addFace(mData.SequenceType), index, "aligned")
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256 index = index + 1
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257 n.add_face(addFace(mData.CarbapenemResistanceGenes), index, "aligned")
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258 index = index + 1
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259 for i in range(len(distanceDict[list(distanceDict.keys())[0]])): #this loop adds distance matrix
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260 n.add_face(addFace(list(distanceDict[n.name])[i]), index + i, "aligned")
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261
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262 t.render("./tree.pdf", w=5000,units="mm", tree_style=ts) #save it as a png. or an phyloxml
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263
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264 #endregion
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265 #endregion
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266
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267
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268 start = time.time()#time the analysis
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269
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270 #analysis time
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271 Main()
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272
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273 end = time.time()
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274 print("Finished!\nThe analysis used: " + str(end-start) + " seconds")
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