Mercurial > repos > proteore > proteore_data_manager

annotate data_manager/resource_building.py @ 53:bb552aa4b9ac draft

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"planemo upload commit 59b014e9f6e2d668cbd7c4844b10db3d59baefd8-dirty"
author proteore
date Fri, 05 Jun 2020 13:49:53 +0000
parents 55b12ec24a9f
children 109fc5236204
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1 # -*- coding: utf-8 -*-
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2 """
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3 The purpose of this script is to create source files from different databases to be used in other proteore tools
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4 """
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5
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6 import os, shutil, sys, argparse, requests, time, csv, re, json, shutil, zipfile, subprocess
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7 from io import BytesIO
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8 from zipfile import ZipFile
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9 from galaxy.util.json import from_json_string, to_json_string
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10
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11 #######################################################################################################
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12 # General functions
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13 #######################################################################################################
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14 def unzip(url, output_file):
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15 """
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16 Get a zip file content from a link and unzip
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17 """
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18 content = requests.get(url)
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19 zipfile = ZipFile(BytesIO(content.content))
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20 output_content = ""
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21 output_content += zipfile.open(zipfile.namelist()[0]).read()
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22 output = open(output_file, "w")
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23 output.write(output_content)
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24 output.close()
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25
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26 def _add_data_table_entry(data_manager_dict, data_table_entry,data_table):
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27 data_manager_dict['data_tables'] = data_manager_dict.get('data_tables', {})
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28 data_manager_dict['data_tables'][data_table] = data_manager_dict['data_tables'].get(data_table, [])
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29 data_manager_dict['data_tables'][data_table].append(data_table_entry)
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30 return data_manager_dict
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31
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32 #######################################################################################################
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33 # 1. Human Protein Atlas
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34 # - Normal tissue
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35 # - Pathology
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36 # - Full Atlas
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37 #######################################################################################################
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38 def HPA_sources(data_manager_dict, tissue, target_directory):
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39 if tissue == "HPA_normal_tissue":
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40 tissue_name = "HPA normal tissue"
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41 url = "https://www.proteinatlas.org/download/normal_tissue.tsv.zip"
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42 table = "proteore_protein_atlas_normal_tissue"
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43 elif tissue == "HPA_pathology":
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44 tissue_name = "HPA pathology"
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45 url = "https://www.proteinatlas.org/download/pathology.tsv.zip"
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46 table = "proteore_protein_atlas_tumor_tissue"
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47 elif tissue == "HPA_full_atlas":
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48 tissue_name = "HPA full atlas"
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49 url = "https://www.proteinatlas.org/download/proteinatlas.tsv.zip"
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50 table = "proteore_protein_full_atlas"
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51 elif tissue == "HPA_RNA_tissue":
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52 tissue_name = "HPA RNA tissue"
50
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53 url = "https://www.proteinatlas.org/download/rna_tissue_consensus.tsv.zip"
48
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54 table = "proteore_protein_atlas_rna_tissue"
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55
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56 output_file = tissue +"_"+ time.strftime("%d-%m-%Y") + ".tsv"
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57 path = os.path.join(target_directory, output_file)
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58 unzip(url, path) #download and save file
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59 tissue_name = tissue_name + " " + time.strftime("%d/%m/%Y")
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60 release = tissue_name.replace(" ","_").replace("/","-")
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61 id = str(10000000000 - int(time.strftime("%Y%m%d")))
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62
1
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63
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64 data_table_entry = dict(id=id, release=release, name = tissue_name, tissue = tissue, value = path)
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65 _add_data_table_entry(data_manager_dict, data_table_entry, table)
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66
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67
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68 #######################################################################################################
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69 # 2. Peptide Atlas
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70 #######################################################################################################
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71 def peptide_atlas_sources(data_manager_dict, tissue, date, target_directory):
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72 # Define organism_id (here Human) - to be upraded when other organism added to the project
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73 organism_id = "2"
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74 # Extract sample_category_id and output filename
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75 tissue=tissue.split(".")
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76 sample_category_id = tissue[0]
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77 tissue_name = tissue[1]
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78 output_file = tissue_name+"_"+date + ".tsv"
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79
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80 query="https://db.systemsbiology.net/sbeams/cgi/PeptideAtlas/GetProteins?&atlas_build_id="+ \
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81 sample_category_id+"&display_options=ShowAbundances&organism_id="+organism_id+ \
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82 "&redundancy_constraint=4&presence_level_constraint=1%2C2&gene_annotation_level_constraint=leaf\
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83 &QUERY_NAME=AT_GetProteins&action=QUERY&output_mode=tsv&apply_action=QUERY"
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84
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85 with requests.Session() as s:
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86 download = s.get(query)
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87 decoded_content = download.content.decode('utf-8')
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88 cr = csv.reader(decoded_content.splitlines(), delimiter='\t')
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89
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90 uni_dict = build_dictionary(cr)
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91
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92 #columns of data table peptide_atlas
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93 tissue_id = tissue_name+"_"+date
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94 name = tissue_id.replace("-","/").replace("_"," ")
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95 path = os.path.join(target_directory,output_file)
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96
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97 with open(path,"w") as out :
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98 w = csv.writer(out,delimiter='\t')
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99 w.writerow(["Uniprot_AC","nb_obs"])
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100 w.writerows(uni_dict.items())
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101
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102 data_table_entry = dict(id=tissue_id, name=name, value = path, tissue = tissue_name)
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103 _add_data_table_entry(data_manager_dict, data_table_entry, "proteore_peptide_atlas")
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104
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105 #function to count the number of observations by uniprot id
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106 def build_dictionary (csv) :
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107 uni_dict = {}
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108 for line in csv :
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109 if "-" not in line[0] and check_uniprot_access(line[0]) :
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110 if line[0] in uni_dict :
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111 uni_dict[line[0]] += int(line[5])
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112 else :
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113 uni_dict[line[0]] = int(line[5])
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114
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115 return uni_dict
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116
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117 #function to check if an id is an uniprot accession number : return True or False-
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118 def check_uniprot_access (id) :
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119 uniprot_pattern = re.compile("[OPQ][0-9][A-Z0-9]{3}[0-9]|[A-NR-Z][0-9]([A-Z][A-Z0-9]{2}[0-9]){1,2}")
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120 if uniprot_pattern.match(id) :
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121 return True
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122 else :
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123 return False
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124
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125 def check_entrez_geneid (id) :
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126 entrez_pattern = re.compile("[0-9]+|[A-Z]{1,2}_[0-9]+|[A-Z]{1,2}_[A-Z]{1,4}[0-9]+")
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127 if entrez_pattern.match(id) :
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128 return True
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129 else :
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130 return False
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131
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132 #######################################################################################################
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133 # 3. ID mapping file
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134 #######################################################################################################
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135 import ftplib, gzip
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136 from io import StringIO
0
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137 csv.field_size_limit(sys.maxsize) # to handle big files
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138
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139 def id_mapping_sources (data_manager_dict, species, target_directory, tool_data_path) :
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140
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141 human = species == "Human"
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142 species_dict = { "Human" : "HUMAN_9606", "Mouse" : "MOUSE_10090", "Rat" : "RAT_10116" }
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143 files=["idmapping_selected.tab.gz","idmapping.dat.gz"]
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144 archive = os.path.join(tool_data_path, "id_mapping/ID_mapping_archive_"+species+"_"+str(time.strftime("%Y%m%d")))
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145 if os.path.isdir(archive) is False : os.mkdir(archive)
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146
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147 #header
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148 if human : tab = [["UniProt-AC","UniProt-AC_reviewed","UniProt-ID","GeneID","RefSeq","GI","PDB","GO","PIR","MIM","UniGene","Ensembl_Gene","Ensembl_Transcript","Ensembl_Protein","neXtProt","BioGrid","STRING","KEGG",'Gene_Name']]
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149 else : tab = [["UniProt-AC","UniProt-AC_reviewed","UniProt-ID","GeneID","RefSeq","GI","PDB","GO","PIR","MIM","UniGene","Ensembl_Gene","Ensembl_Transcript","Ensembl_Protein","BioGrid","STRING","KEGG",'Gene_Name']]
0
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150
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151 #get selected.tab and keep only ids of interest
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152 selected_tab_file=species_dict[species]+"_"+files[0]
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153 tab_path = download_from_uniprot_ftp(selected_tab_file,target_directory)
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154 with gzip.open(tab_path,"rt") as select :
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155 tab_reader = csv.reader(select,delimiter="\t")
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156 for line in tab_reader :
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157 tab.append([line[0]]+[line[i] for i in [0,1,2,3,4,5,6,11,13,14,18,19,20]])
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158 if os.path.exists(os.path.join(archive,tab_path.split("/")[-1])) : os.remove(os.path.join(archive,tab_path.split("/")[-1]))
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159 shutil.move(tab_path, archive)
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160 #print("selected_tab ok")
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161
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162 #get uniprot-AC reviewed
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163 organism = species_dict[species].split("_")[1]
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164 query = "https://www.uniprot.org/uniprot/?query=reviewed:yes+AND+organism:"+organism+"&format=list"
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165
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166 with requests.Session() as s:
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167 download = s.get(query)
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168 decoded_content = download.content.decode('utf-8')
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169 uniprot_reviewed_list = decoded_content.splitlines()
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170
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171 #save reviewed list
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172 reviewed_list_path = os.path.join(archive,'uniprot_reviewed_list.txt')
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173 with open(reviewed_list_path,'w') as reviewed_list_file:
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174 for id in uniprot_reviewed_list:
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175 reviewed_list_file.write(id+"\n")
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176
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177 #remove unreviewed uniprot-AC
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178 for line in tab[1:]:
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179 UniProtAC = line[1]
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180 if UniProtAC not in uniprot_reviewed_list :
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181 line[1]=""
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182
0
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183 """
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184 Supplementary ID to get from HUMAN_9606_idmapping.dat :
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185 -NextProt,BioGrid,STRING,KEGG
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186 """
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187
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188 #there's more id type for human
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189 if human : ids = ['neXtProt','BioGrid','STRING','KEGG','Gene_Name' ] #ids to get from dat_file
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190 else : ids = ['BioGrid','STRING','KEGG','Gene_Name' ]
0
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191 unidict = {}
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192
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193 #keep only ids of interest in dictionaries
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194 dat_file = species_dict[species]+"_"+files[1]
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195 dat_path = download_from_uniprot_ftp(dat_file,target_directory)
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196 with gzip.open(dat_path,"rt") as dat :
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197 dat_reader = csv.reader(dat,delimiter="\t")
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198 for line in dat_reader :
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199 uniprotID=line[0] #UniProtID as key
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200 id_type=line[1] #ID type of corresponding id, key of sub-dictionnary
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201 cor_id=line[2] #corresponding id
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202 if "-" not in id_type : #we don't keep isoform
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203 if id_type in ids and uniprotID in unidict :
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204 if id_type in unidict[uniprotID] :
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205 unidict[uniprotID][id_type]= ";".join([unidict[uniprotID][id_type],cor_id]) #if there is already a value in the dictionnary
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206 else :
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207 unidict[uniprotID].update({ id_type : cor_id })
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208 elif id_type in ids :
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209 unidict[uniprotID]={id_type : cor_id}
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210 if os.path.exists(os.path.join(archive,dat_path.split("/")[-1])) : os.remove(os.path.join(archive,dat_path.split("/")[-1]))
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211 shutil.move(dat_path, archive)
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212
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213 #print("dat_file ok")
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214
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215 #add ids from idmapping.dat to the final tab
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216 for line in tab[1:] :
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217 uniprotID=line[0]
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218 if human :
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219 if uniprotID in unidict :
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220 nextprot = access_dictionary(unidict,uniprotID,'neXtProt')
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221 if nextprot != '' : nextprot = clean_nextprot_id(nextprot,line[0])
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222 line.extend([nextprot,access_dictionary(unidict,uniprotID,'BioGrid'),access_dictionary(unidict,uniprotID,'STRING'),
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223 access_dictionary(unidict,uniprotID,'KEGG'),access_dictionary(unidict,uniprotID,'Gene_Name')])
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224 else :
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225 line.extend(["","","","",""])
0
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226 else :
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227 if uniprotID in unidict :
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228 line.extend([access_dictionary(unidict,uniprotID,'BioGrid'),access_dictionary(unidict,uniprotID,'STRING'),
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229 access_dictionary(unidict,uniprotID,'KEGG'),access_dictionary(unidict,uniprotID,'Gene_Name')])
0
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230 else :
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231 line.extend(["","","",""])
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232
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233 #print ("tab ok")
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234
20
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235 #add missing nextprot ID for human or replace old ones
0
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236 if human :
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237 #build next_dict
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238 nextprot_path = id_list_from_nextprot_ftp("nextprot_ac_list_all.txt",target_directory)
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239 with open(nextprot_path,'r') as nextprot_ids :
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240 nextprot_ids = nextprot_ids.read().splitlines()
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parents: 40
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241 if os.path.exists(os.path.join(archive,nextprot_path.split("/")[-1])) : os.remove(os.path.join(archive,nextprot_path.split("/")[-1]))
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parents: 30
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242 shutil.move(nextprot_path,archive)
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parents:
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243 next_dict = {}
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244 for nextid in nextprot_ids :
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245 next_dict[nextid.replace("NX_","")] = nextid
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246 #os.remove(os.path.join(target_directory,"nextprot_ac_list_all.txt"))
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247
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248 #add missing nextprot ID
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249 for line in tab[1:] :
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250 uniprotID=line[0]
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251 nextprotID=line[14]
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252 if uniprotID in next_dict and (nextprotID == '' or (nextprotID != "NX_"+uniprotID and next_dict[uniprotID] == "NX_"+uniprotID)) :
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253 line[14]=next_dict[uniprotID]
0
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254
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255 output_file = species+"_id_mapping_"+ time.strftime("%d-%m-%Y") + ".tsv"
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256 path = os.path.join(target_directory,output_file)
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257
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258 with open(path,"w") as out :
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259 w = csv.writer(out,delimiter='\t')
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260 w.writerows(tab)
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parents: 30
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261
36
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parents: 35
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262 subprocess.call(['tar', '-czvf', archive+".tar.gz", archive])
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263 shutil.rmtree(archive, ignore_errors=True)
0
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264
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265 name_dict={"Human" : "Homo sapiens", "Mouse" : "Mus musculus", "Rat" : "Rattus norvegicus"}
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266 name = species +" (" + name_dict[species]+" "+time.strftime("%d/%m/%Y")+")"
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267 release = species+"_id_mapping_"+ time.strftime("%d-%m-%Y")
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parents: 22
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268 id = str(10000000000 - int(time.strftime("%Y%m%d"))) #new ids must be inferior to previous id -> sort by <filter> in xml only in descending order
0
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269
21
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270 data_table_entry = dict(id=id, release=release , name = name, species = species, value = path)
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271 _add_data_table_entry(data_manager_dict, data_table_entry, "proteore_id_mapping_"+species)
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272
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273 def download_from_uniprot_ftp(file,target_directory) :
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274 ftp_dir = "pub/databases/uniprot/current_release/knowledgebase/idmapping/by_organism/"
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275 path = os.path.join(target_directory, file)
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276 ftp = ftplib.FTP("ftp.uniprot.org")
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277 ftp.login("anonymous", "anonymous")
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278 ftp.cwd(ftp_dir)
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279 ftp.retrbinary("RETR " + file, open(path, 'wb').write)
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280 ftp.quit()
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281 return (path)
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282
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283 def id_list_from_nextprot_ftp(file,target_directory) :
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284 ftp_dir = "pub/current_release/ac_lists/"
0
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285 path = os.path.join(target_directory, file)
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286 ftp = ftplib.FTP("ftp.nextprot.org")
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287 ftp.login("anonymous", "anonymous")
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288 ftp.cwd(ftp_dir)
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289 ftp.retrbinary("RETR " + file, open(path, 'wb').write)
0
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290 ftp.quit()
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291 with open(path,'r') as nextprot_ids :
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292 nextprot_ids = nextprot_ids.read().splitlines()
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293 return (nextprot_ids)
0
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294
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295 #return '' if there's no value in a dictionary, avoid error
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296 def access_dictionary (dico,key1,key2) :
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297 if key1 in dico :
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298 if key2 in dico[key1] :
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299 return (dico[key1][key2])
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300 else :
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301 return ("")
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302 #print (key2,"not in ",dico,"[",key1,"]")
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303 else :
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304 return ('')
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305
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306 #if there are several nextprot ID for one uniprotID, return the uniprot like ID
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307 def clean_nextprot_id (next_id,uniprotAc) :
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308 if len(next_id.split(";")) > 1 :
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309 tmp = next_id.split(";")
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310 if "NX_"+uniprotAc in tmp :
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parents:
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311 return ("NX_"+uniprotAc)
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312 else :
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313 return (tmp[1])
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314 else :
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315 return (next_id)
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316
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317
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318 #######################################################################################################
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319 # 4. Build protein interaction maps files
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320 #######################################################################################################
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321
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322 def get_interactant_name(line,dico):
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323
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324 if line[0] in dico :
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325 interactant_A = dico[line[0]]
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326 else :
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327 interactant_A = "NA"
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328
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329 if line[1] in dico :
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330 interactant_B = dico[line[1]]
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331 else :
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332 interactant_B = "NA"
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333
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334 return interactant_A, interactant_B
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335
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336 def PPI_ref_files(data_manager_dict, species, interactome, target_directory):
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337
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338 species_dict={'Human':'Homo sapiens',"Mouse":"Mus musculus","Rat":"Rattus norvegicus"}
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parents:
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339
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340 ##BioGRID
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341 if interactome=="biogrid":
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parents:
diff changeset
342
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proteore
parents:
diff changeset
343 tab2_link="https://downloads.thebiogrid.org/Download/BioGRID/Release-Archive/BIOGRID-3.5.167/BIOGRID-ORGANISM-3.5.167.tab2.zip"
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proteore
parents:
diff changeset
344
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proteore
parents:
diff changeset
345 #download zip file
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proteore
parents:
diff changeset
346 r = requests.get(tab2_link)
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proteore
parents:
diff changeset
347 with open("BioGRID.zip", "wb") as code:
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proteore
parents:
diff changeset
348 code.write(r.content)
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proteore
parents:
diff changeset
349
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proteore
parents:
diff changeset
350 #unzip files
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proteore
parents:
diff changeset
351 with zipfile.ZipFile("BioGRID.zip", 'r') as zip_ref:
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proteore
parents:
diff changeset
352 if not os.path.exists("tmp_BioGRID"): os.makedirs("tmp_BioGRID")
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proteore
parents:
diff changeset
353 zip_ref.extractall("tmp_BioGRID")
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proteore
parents:
diff changeset
354
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proteore
parents:
diff changeset
355 #import file of interest and build dictionary
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proteore
parents:
diff changeset
356 file_path="tmp_BioGRID/BIOGRID-ORGANISM-"+species_dict[species].replace(" ","_")+"-3.5.167.tab2.txt"
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proteore
parents:
diff changeset
357 with open(file_path,"r") as handle :
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proteore
parents:
diff changeset
358 tab_file = csv.reader(handle,delimiter="\t")
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proteore
parents:
diff changeset
359 dico_network = {}
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proteore
parents:
diff changeset
360 GeneID_index=1
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proteore
parents:
diff changeset
361 network_cols=[1,2,7,8,11,12,14,18,20]
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proteore
parents:
diff changeset
362 for line in tab_file :
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proteore
parents:
diff changeset
363 if line[GeneID_index] not in dico_network:
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proteore
parents:
diff changeset
364 dico_network[line[GeneID_index]]=[[line[i] for i in network_cols]]
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proteore
parents:
diff changeset
365 else:
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proteore
parents:
diff changeset
366 dico_network[line[GeneID_index]].append([line[i] for i in network_cols])
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proteore
parents:
diff changeset
367
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proteore
parents:
diff changeset
368 #delete tmp_BioGRID directory
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proteore
parents:
diff changeset
369 os.remove("BioGRID.zip")
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proteore
parents:
diff changeset
370 shutil.rmtree("tmp_BioGRID", ignore_errors=True)
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proteore
parents:
diff changeset
371
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proteore
parents:
diff changeset
372 #download NCBI2Reactome.txt file and build dictionary
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proteore
parents:
diff changeset
373 with requests.Session() as s:
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proteore
parents:
diff changeset
374 r = s.get('https://www.reactome.org/download/current/NCBI2Reactome.txt')
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proteore
parents:
diff changeset
375 r.encoding ="utf-8"
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proteore
parents:
diff changeset
376 tab_file = csv.reader(r.content.splitlines(), delimiter='\t')
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proteore
parents:
diff changeset
377
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proteore
parents:
diff changeset
378 dico_nodes = {}
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proteore
parents:
diff changeset
379 geneid_index=0
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proteore
parents:
diff changeset
380 pathway_description_index=3
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proteore
parents:
diff changeset
381 species_index=5
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proteore
parents:
diff changeset
382 for line in tab_file :
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proteore
parents:
diff changeset
383 if line[species_index]==species_dict[species]:
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proteore
parents:
diff changeset
384 if line[geneid_index] in dico_nodes :
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proteore
parents:
diff changeset
385 dico_nodes[line[geneid_index]].append(line[pathway_description_index])
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proteore
parents:
diff changeset
386 else :
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proteore
parents:
diff changeset
387 dico_nodes[line[geneid_index]] = [line[pathway_description_index]]
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proteore
parents:
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388
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proteore
parents:
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389 dico={}
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proteore
parents:
diff changeset
390 dico['network']=dico_network
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proteore
parents:
diff changeset
391 dico['nodes']=dico_nodes
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proteore
parents:
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392
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proteore
parents:
diff changeset
393 ##Bioplex
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proteore
parents:
diff changeset
394 elif interactome=="bioplex":
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proteore
parents:
diff changeset
395
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proteore
parents:
diff changeset
396 with requests.Session() as s:
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proteore
parents:
diff changeset
397 r = s.get('http://bioplex.hms.harvard.edu/data/BioPlex_interactionList_v4a.tsv')
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proteore
parents:
diff changeset
398 r = r.content.decode('utf-8')
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proteore
parents:
diff changeset
399 bioplex = csv.reader(r.splitlines(), delimiter='\t')
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proteore
parents:
diff changeset
400
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proteore
parents:
diff changeset
401 dico_network = {}
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proteore
parents:
diff changeset
402 dico_network["GeneID"]={}
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proteore
parents:
diff changeset
403 network_geneid_cols=[0,1,4,5,8]
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proteore
parents:
diff changeset
404 dico_network["UniProt-AC"]={}
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proteore
parents:
diff changeset
405 network_uniprot_cols=[2,3,4,5,8]
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proteore
parents:
diff changeset
406 dico_GeneID_to_UniProt = {}
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proteore
parents:
diff changeset
407 for line in bioplex :
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proteore
parents:
diff changeset
408 if line[0] not in dico_network["GeneID"]:
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proteore
parents:
diff changeset
409 dico_network["GeneID"][line[0]]=[[line[i] for i in network_geneid_cols]]
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proteore
parents:
diff changeset
410 else :
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proteore
parents:
diff changeset
411 dico_network["GeneID"][line[0]].append([line[i] for i in network_geneid_cols])
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proteore
parents:
diff changeset
412 if line[1] not in dico_network["UniProt-AC"]:
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proteore
parents:
diff changeset
413 dico_network["UniProt-AC"][line[2]]=[[line[i] for i in network_uniprot_cols]]
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proteore
parents:
diff changeset
414 else:
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proteore
parents:
diff changeset
415 dico_network["UniProt-AC"][line[2]].append([line[i] for i in network_uniprot_cols])
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proteore
parents:
diff changeset
416 dico_GeneID_to_UniProt[line[0]]=line[2]
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proteore
parents:
diff changeset
417
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proteore
parents:
diff changeset
418 with requests.Session() as s:
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proteore
parents:
diff changeset
419 r = s.get('https://reactome.org/download/current/UniProt2Reactome.txt')
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proteore
parents:
diff changeset
420 r.encoding ="utf-8"
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
421 tab_file = csv.reader(r.content.splitlines(), delimiter='\t')
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proteore
parents:
diff changeset
422
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proteore
parents:
diff changeset
423 dico_nodes_uniprot = {}
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proteore
parents:
diff changeset
424 uniProt_index=0
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proteore
parents:
diff changeset
425 pathway_description_index=3
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proteore
parents:
diff changeset
426 species_index=5
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proteore
parents:
diff changeset
427 for line in tab_file :
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proteore
parents:
diff changeset
428 if line[species_index]==species_dict[species]:
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proteore
parents:
diff changeset
429 if line[uniProt_index] in dico_nodes_uniprot :
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proteore
parents:
diff changeset
430 dico_nodes_uniprot[line[uniProt_index]].append(line[pathway_description_index])
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proteore
parents:
diff changeset
431 else :
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proteore
parents:
diff changeset
432 dico_nodes_uniprot[line[uniProt_index]] = [line[pathway_description_index]]
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proteore
parents:
diff changeset
433
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proteore
parents:
diff changeset
434 with requests.Session() as s:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
435 r = s.get('https://www.reactome.org/download/current/NCBI2Reactome.txt')
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
436 r.encoding ="utf-8"
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
437 tab_file = csv.reader(r.content.splitlines(), delimiter='\t')
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proteore
parents:
diff changeset
438
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proteore
parents:
diff changeset
439 dico_nodes_geneid = {}
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proteore
parents:
diff changeset
440 geneid_index=0
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proteore
parents:
diff changeset
441 pathway_description_index=3
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proteore
parents:
diff changeset
442 species_index=5
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proteore
parents:
diff changeset
443 for line in tab_file :
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proteore
parents:
diff changeset
444 if line[species_index]==species_dict[species]:
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proteore
parents:
diff changeset
445 if line[geneid_index] in dico_nodes_geneid :
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proteore
parents:
diff changeset
446 dico_nodes_geneid[line[geneid_index]].append(line[pathway_description_index])
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proteore
parents:
diff changeset
447 else :
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proteore
parents:
diff changeset
448 dico_nodes_geneid[line[geneid_index]] = [line[pathway_description_index]]
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proteore
parents:
diff changeset
449
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proteore
parents:
diff changeset
450 dico={}
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proteore
parents:
diff changeset
451 dico_nodes={}
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proteore
parents:
diff changeset
452 dico_nodes['GeneID']=dico_nodes_geneid
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proteore
parents:
diff changeset
453 dico_nodes['UniProt-AC']=dico_nodes_uniprot
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proteore
parents:
diff changeset
454 dico['network']=dico_network
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proteore
parents:
diff changeset
455 dico['nodes']=dico_nodes
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proteore
parents:
diff changeset
456 dico['convert']=dico_GeneID_to_UniProt
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proteore
parents:
diff changeset
457
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proteore
parents:
diff changeset
458 ##Humap
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parents:
diff changeset
459 elif interactome=="humap":
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parents:
diff changeset
460
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parents:
diff changeset
461 with requests.Session() as s:
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parents:
diff changeset
462 r = s.get('http://proteincomplexes.org/static/downloads/nodeTable.txt')
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proteore
parents:
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463 r = r.content.decode('utf-8')
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proteore
parents:
diff changeset
464 humap_nodes = csv.reader(r.splitlines(), delimiter=',')
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parents:
diff changeset
465
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parents:
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466 dico_geneid_to_gene_name={}
9
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parents: 8
diff changeset
467 dico_protein_name={}
0
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parents:
diff changeset
468 for line in humap_nodes :
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proteore
parents:
diff changeset
469 if check_entrez_geneid(line[4]):
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proteore
parents:
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470 if line[4] not in dico_geneid_to_gene_name:
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proteore
parents:
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471 dico_geneid_to_gene_name[line[4]]=line[3]
9
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parents: 8
diff changeset
472 if line[4] not in dico_protein_name:
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parents: 8
diff changeset
473 dico_protein_name[line[4]]=line[5]
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parents: 8
diff changeset
474
0
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proteore
parents:
diff changeset
475 with requests.Session() as s:
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proteore
parents:
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476 r = s.get('http://proteincomplexes.org/static/downloads/pairsWprob.txt')
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proteore
parents:
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477 r = r.content.decode('utf-8')
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parents:
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478 humap = csv.reader(r.splitlines(), delimiter='\t')
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parents:
diff changeset
479
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parents:
diff changeset
480 dico_network = {}
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proteore
parents:
diff changeset
481 for line in humap :
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proteore
parents:
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482 if check_entrez_geneid(line[0]) and check_entrez_geneid(line[1]):
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proteore
parents:
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483
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484 interactant_A, interactant_B = get_interactant_name(line,dico_geneid_to_gene_name)
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485
4
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diff changeset
486 #first interactant (first column)
0
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parents:
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487 if line[0] not in dico_network:
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proteore
parents:
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488 dico_network[line[0]]=[line[:2]+[interactant_A,interactant_B,line[2]]]
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parents:
diff changeset
489 else :
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parents:
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490 dico_network[line[0]].append(line[:2]+[interactant_A,interactant_B,line[2]])
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parents:
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491
4
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parents: 3
diff changeset
492 #second interactant (second column)
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parents: 3
diff changeset
493 if line[1] not in dico_network:
5
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parents: 4
diff changeset
494 dico_network[line[1]]=[[line[1],line[0],interactant_B,interactant_A,line[2]]]
4
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parents: 3
diff changeset
495 else :
5
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parents: 4
diff changeset
496 dico_network[line[1]].append([line[1],line[0],interactant_B,interactant_A,line[2]])
4
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parents: 3
diff changeset
497
0
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proteore
parents:
diff changeset
498 with requests.Session() as s:
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proteore
parents:
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499 r = s.get('https://www.reactome.org/download/current/NCBI2Reactome.txt')
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proteore
parents:
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500 r.encoding ="utf-8"
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parents:
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501 tab_file = csv.reader(r.content.splitlines(), delimiter='\t')
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proteore
parents:
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502
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parents:
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503 dico_nodes = {}
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proteore
parents:
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504 geneid_index=0
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proteore
parents:
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505 pathway_description_index=3
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proteore
parents:
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506 species_index=5
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parents:
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507 for line in tab_file :
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proteore
parents:
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508 if line[species_index]==species_dict[species]:
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parents:
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509 #Fill dictionary with pathways
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parents:
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510 if line[geneid_index] in dico_nodes :
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parents:
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511 dico_nodes[line[geneid_index]].append(line[pathway_description_index])
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parents:
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512 else :
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parents:
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513 dico_nodes[line[geneid_index]] = [line[pathway_description_index]]
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parents:
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514
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515 dico={}
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516 dico['network']=dico_network
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parents:
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517 dico['nodes']=dico_nodes
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parents:
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518 dico['gene_name']=dico_geneid_to_gene_name
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diff changeset
519 dico['protein_name']=dico_protein_name
0
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parents:
diff changeset
520
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521 #writing output
27
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diff changeset
522 output_file = species+'_'+interactome+'_'+ time.strftime("%Y-%m-%d") + ".json"
0
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parents:
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523 path = os.path.join(target_directory,output_file)
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parents:
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524 name = species+" ("+species_dict[species]+") "+time.strftime("%d/%m/%Y")
27
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parents: 26
diff changeset
525 release = species+"_"+interactome+"_"+ time.strftime("%Y-%m-%d")
26
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parents: 24
diff changeset
526 id = str(10000000000 - int(time.strftime("%Y%m%d")))
0
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parents:
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527
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parents:
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528 with open(path, 'w') as handle:
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parents:
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529 json.dump(dico, handle, sort_keys=True)
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parents:
diff changeset
530
26
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parents: 24
diff changeset
531 data_table_entry = dict(id=id, release=release, name = name, species = species, value = path)
0
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parents:
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532 _add_data_table_entry(data_manager_dict, data_table_entry, "proteore_"+interactome+"_dictionaries")
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parents:
diff changeset
533
6
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parents: 5
diff changeset
534 #######################################################################################################
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parents: 5
diff changeset
535 # 5. nextprot (add protein features)
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parents: 5
diff changeset
536 #######################################################################################################
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parents: 5
diff changeset
537
8
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parents: 6
diff changeset
538 def Build_nextprot_ref_file(data_manager_dict,target_directory):
6
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
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parents: 5
diff changeset
539 nextprot_ids_file = "nextprot_ac_list_all.txt"
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parents: 5
diff changeset
540 ids = id_list_from_nextprot_ftp(nextprot_ids_file,target_directory)
12
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parents: 11
diff changeset
541
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parents: 11
diff changeset
542 output_file = 'nextprot_ref_'+ time.strftime("%d-%m-%Y") + ".tsv"
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proteore
parents: 11
diff changeset
543 path = os.path.join(target_directory,output_file)
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proteore
parents: 11
diff changeset
544 name = "neXtProt release "+time.strftime("%d-%m-%Y")
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proteore
parents: 15
diff changeset
545 release_id = "nextprot_ref_"+time.strftime("%d-%m-%Y")
12
f6afaa1f562c planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c-dirty
proteore
parents: 11
diff changeset
546
13
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parents: 12
diff changeset
547 output = open(path, 'w')
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parents: 12
diff changeset
548 writer = csv.writer(output,delimiter="\t")
12
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proteore
parents: 11
diff changeset
549
6
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proteore
parents: 5
diff changeset
550 nextprot_file=[["NextprotID","MW","SeqLength","IsoPoint","Chr","SubcellLocations","Diseases","TMDomains","ProteinExistence"]]
14
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parents: 13
diff changeset
551 writer.writerows(nextprot_file)
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parents: 13
diff changeset
552
6
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parents: 5
diff changeset
553 for id in ids :
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
554 query="https://api.nextprot.org/entry/"+id+".json"
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proteore
parents: 5
diff changeset
555 resp = requests.get(url=query)
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parents: 5
diff changeset
556 data = resp.json()
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parents: 5
diff changeset
557
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parents: 5
diff changeset
558 #get info from json dictionary
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parents: 5
diff changeset
559 mass_mol = data["entry"]["isoforms"][0]["massAsString"]
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
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parents: 5
diff changeset
560 seq_length = data['entry']["isoforms"][0]["sequenceLength"]
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proteore
parents: 5
diff changeset
561 iso_elec_point = data['entry']["isoforms"][0]["isoelectricPointAsString"]
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
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parents: 5
diff changeset
562 chr_loc = data['entry']["chromosomalLocations"][0]["chromosome"]
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
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parents: 5
diff changeset
563 protein_existence = "PE"+str(data['entry']["overview"]['proteinExistence']['level'])
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parents: 5
diff changeset
564
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parents: 5
diff changeset
565 #put all subcell loc in a set
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proteore
parents: 5
diff changeset
566 if "subcellular-location" in data['entry']["annotationsByCategory"].keys() :
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
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parents: 5
diff changeset
567 subcell_locs = data['entry']["annotationsByCategory"]["subcellular-location"]
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proteore
parents: 5
diff changeset
568 all_subcell_locs = set()
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
569 for loc in subcell_locs :
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proteore
parents: 5
diff changeset
570 all_subcell_locs.add(loc['cvTermName'])
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parents: 5
diff changeset
571 all_subcell_locs.discard("")
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parents: 5
diff changeset
572 all_subcell_locs = ";".join(all_subcell_locs)
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parents: 5
diff changeset
573 else :
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
574 all_subcell_locs = "NA"
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
575
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
576 #put all subcell loc in a set
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
577 if ('disease') in data['entry']['annotationsByCategory'].keys() :
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
578 diseases = data['entry']['annotationsByCategory']['disease']
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
579 all_diseases = set()
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
580 for disease in diseases :
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
581 if (disease['cvTermName'] is not None and disease['cvTermName'] != ""):
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
582 all_diseases.add(disease['cvTermName'])
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
583 if len(all_diseases) > 0 : all_diseases = ";".join(all_diseases)
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
584 else : all_diseases="NA"
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
585 else :
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
586 all_diseases="NA"
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
587
11
ac2cd728c40e planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c
proteore
parents: 9
diff changeset
588 #get all tm domain
6
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
589 nb_domains = 0
11
ac2cd728c40e planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c
proteore
parents: 9
diff changeset
590 if "transmembrane-region" in data['entry']['annotationsByCategory'].keys():
ac2cd728c40e planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c
proteore
parents: 9
diff changeset
591 tm_domains = data['entry']['annotationsByCategory']["transmembrane-region"]
ac2cd728c40e planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c
proteore
parents: 9
diff changeset
592 all_tm_domains = set()
ac2cd728c40e planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c
proteore
parents: 9
diff changeset
593 for tm in tm_domains :
ac2cd728c40e planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c
proteore
parents: 9
diff changeset
594 all_tm_domains.add(tm['cvTermName'])
ac2cd728c40e planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c
proteore
parents: 9
diff changeset
595 nb_domains+=1
24
6cbb76823b7b planemo upload commit 3e8aad84b7fe9218370364b1aef3ea5779475f9f-dirty
proteore
parents: 23
diff changeset
596 #print "nb domains ++"
6cbb76823b7b planemo upload commit 3e8aad84b7fe9218370364b1aef3ea5779475f9f-dirty
proteore
parents: 23
diff changeset
597 #print (nb_domains)
15
5f39d3ef5fe3 planemo upload commit 45108c8cbeeccab12031bbf6e65f1177222d4e10
proteore
parents: 14
diff changeset
598 nextprot_file[:] = []
12
f6afaa1f562c planemo upload commit 39a9e2bf22b07beeca3fb77d86cda25820eb309c-dirty
proteore
parents: 11
diff changeset
599 nextprot_file.append([id,mass_mol,str(seq_length),iso_elec_point,chr_loc,all_subcell_locs,all_diseases,str(nb_domains),protein_existence])
6
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
600 writer.writerows(nextprot_file)
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
601
24
6cbb76823b7b planemo upload commit 3e8aad84b7fe9218370364b1aef3ea5779475f9f-dirty
proteore
parents: 23
diff changeset
602 id = str(10000000000 - int(time.strftime("%Y%m%d")))
6cbb76823b7b planemo upload commit 3e8aad84b7fe9218370364b1aef3ea5779475f9f-dirty
proteore
parents: 23
diff changeset
603
6cbb76823b7b planemo upload commit 3e8aad84b7fe9218370364b1aef3ea5779475f9f-dirty
proteore
parents: 23
diff changeset
604 data_table_entry = dict(id=id, release=release_id, name = name, value = path)
6
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
605 _add_data_table_entry(data_manager_dict, data_table_entry, "proteore_nextprot_ref")
0
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
606
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
607 #######################################################################################################
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
608 # Main function
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
609 #######################################################################################################
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proteore
parents:
diff changeset
610 def main():
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proteore
parents:
diff changeset
611 parser = argparse.ArgumentParser()
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
612 parser.add_argument("--hpa", metavar = ("HPA_OPTION"))
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
613 parser.add_argument("--peptideatlas", metavar=("SAMPLE_CATEGORY_ID"))
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proteore
parents:
diff changeset
614 parser.add_argument("--id_mapping", metavar = ("ID_MAPPING_SPECIES"))
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proteore
parents:
diff changeset
615 parser.add_argument("--interactome", metavar = ("PPI"))
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
616 parser.add_argument("--species")
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
617 parser.add_argument("--date")
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proteore
parents:
diff changeset
618 parser.add_argument("-o", "--output")
6
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
619 parser.add_argument("--database")
31
faeeabb11a4d "planemo upload commit ba867b8fa3352695fbda1ae764407f363ee79a50-dirty"
proteore
parents: 30
diff changeset
620 parser.add_argument("--tool_data_path")
0
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
621 args = parser.parse_args()
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
622
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
623 data_manager_dict = {}
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
624 # Extract json file params
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
625 filename = args.output
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
626 params = from_json_string(open(filename).read())
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
627 target_directory = params[ 'output_data' ][0]['extra_files_path']
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
628 os.mkdir(target_directory)
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proteore
parents:
diff changeset
629
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proteore
parents:
diff changeset
630 ## Download source files from HPA
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proteore
parents:
diff changeset
631 try:
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proteore
parents:
diff changeset
632 hpa = args.hpa
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
633 except NameError:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
634 hpa = None
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
635 if hpa is not None:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
636 #target_directory = "/projet/galaxydev/galaxy/tools/proteore/ProteoRE/tools/resources_building/test-data/"
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
637 hpa = hpa.split(",")
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
638 for hpa_tissue in hpa:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
639 HPA_sources(data_manager_dict, hpa_tissue, target_directory)
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
640
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
641 ## Download source file from Peptide Atlas query
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
642 try:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
643 peptide_atlas = args.peptideatlas
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
644 date = args.date
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
645 except NameError:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
646 peptide_atlas = None
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
647 if peptide_atlas is not None:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
648 #target_directory = "/projet/galaxydev/galaxy/tools/proteore/ProteoRE/tools/resources_building/test-data/"
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
649 peptide_atlas = peptide_atlas.split(",")
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
650 for pa_tissue in peptide_atlas:
32
ec1febc6672e "planemo upload commit ba867b8fa3352695fbda1ae764407f363ee79a50-dirty"
proteore
parents: 31
diff changeset
651 peptide_atlas_sources(data_manager_dict, pa_tissue, date, target_directory)
0
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
652
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
653 ## Download ID_mapping source file from Uniprot
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
654 try:
40
a7bcc9a0a456 "planemo upload commit ba867b8fa3352695fbda1ae764407f363ee79a50-dirty"
proteore
parents: 39
diff changeset
655 id_mapping = args.id_mapping
0
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
656 except NameError:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
657 id_mapping = None
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
658 if id_mapping is not None:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
659 id_mapping = id_mapping .split(",")
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
660 for species in id_mapping :
33
e681d7de4f5e "planemo upload commit ba867b8fa3352695fbda1ae764407f363ee79a50-dirty"
proteore
parents: 32
diff changeset
661 id_mapping_sources(data_manager_dict, species, target_directory, args.tool_data_path)
0
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
662
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
663 ## Download PPI ref files from biogrid/bioplex/humap
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
664 try:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
665 interactome=args.interactome
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
666 if interactome == "biogrid" :
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
667 species=args.species
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
668 else :
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
669 species="Human"
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
670 except NameError:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
671 interactome=None
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
672 species=None
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
673 if interactome is not None and species is not None:
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
674 PPI_ref_files(data_manager_dict, species, interactome, target_directory)
6
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
675
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
676 ## Build nextprot ref file for add protein features
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
677 try:
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
678 database=args.database
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
679 except NameError:
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
680 database=None
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
681 if database is not None :
8
d5badf9de1b0 planemo upload commit 968cd5b4f78f0a1da86fc3bc29f8159f86e199aa-dirty
proteore
parents: 6
diff changeset
682 Build_nextprot_ref_file(data_manager_dict,target_directory)
6
f281a1eb83d6 planemo upload commit 5df487b88ce2146c4be8e1d9f419006583185f6a-dirty
proteore
parents: 5
diff changeset
683
0
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proteore
parents:
diff changeset
684 #save info to json file
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proteore
parents:
diff changeset
685 filename = args.output
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
686 open(filename, 'wb').write(to_json_string(data_manager_dict))
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
687
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proteore
parents:
diff changeset
688 if __name__ == "__main__":
0a26460d7366 planemo upload commit dbc027f59706f5b7d3f9f9319f2652baa50e2df5-dirty
proteore
parents:
diff changeset
689 main()