comparison data_manager/resource_building.py @ 39:ec6252ad1a8e draft

planemo upload commit 43e2a01d7519104c2c16510e4dbdc023e65c49c7-dirty

38:49467e5f78a6

    ##BioGRID
    if interactome=="biogrid":

        tab2_link="https://downloads.thebiogrid.org/Download/BioGRID/Release-Archive/BIOGRID-3.5.167/BIOGRID-ORGANISM-3.5.167.tab2.zip"

        #dowload zip file
        r = requests.get(tab2_link)
        with open("BioGRID.zip", "wb") as code:
            code.write(r.content)
    
        #unzip files

        file_path="tmp_BioGRID/BIOGRID-ORGANISM-"+species_dict[species].replace(" ","_")+"-3.5.167.tab2.txt"
        with open(file_path,"r") as handle :
            tab_file = csv.reader(handle,delimiter="\t")
            dico_network = {}
            GeneID_index=1
            network_cols=[1,2,7,8,11,12,18,20]
            for line in tab_file : 
                if line[GeneID_index] not in dico_network:
                    dico_network[line[GeneID_index]]=[[line[i] for i in network_cols]]
                else:
                    dico_network[line[GeneID_index]].append([line[i] for i in network_cols])

        #delete tmp_BioGRID directory
        os.remove("BioGRID.zip")
        shutil.rmtree("tmp_BioGRID", ignore_errors=True) 

        #download NCBI2Reactome.txt file and build dictionary
        r = requests.get('https://www.reactome.org/download/current/NCBI2Reactome.txt')
        r.encoding ="utf-8"
        tab_file = csv.reader(r.content.splitlines(), delimiter='\t')
        dico_nodes = {}
        GeneID_index=0
        pathway_description_index=3
        species_index=5
        for line in tab_file :
            if line[species_index]==species_dict[species]:
                if line[GeneID_index] in dico_nodes :
                    dico_nodes[line[GeneID_index]].append(line[pathway_description_index])
                else :
                    dico_nodes[line[GeneID_index]] = [line[pathway_description_index]]

        dico={}
        dico['network']=dico_network
        dico['nodes']=dico_nodes

    ##Bioplex
    elif interactome=="bioplex":

        r = requests.get("http://bioplex.hms.harvard.edu/data/BioPlex_interactionList_v4a.tsv")
        r.encoding ="utf-8"
        bioplex = csv.reader(r.content.splitlines(), delimiter='\t')
        dico_network = {}
        dico_network["GeneID"]={}
        network_geneid_cols=[0,1,4,5,8]
        dico_network["UniProt-AC"]={}
        network_uniprot_cols=[2,3,4,5,8]
        dico_GeneID_to_UniProt = {}
        dico_nodes = {}
        for line in bioplex :
            if line[0] not in dico_network["GeneID"]:
                dico_network["GeneID"][line[0]]=[[line[i] for i in network_geneid_cols]]
            else :
                dico_network["GeneID"][line[0]].append([line[i] for i in network_geneid_cols])

                dico_network["UniProt-AC"][line[2]]=[[line[i] for i in network_uniprot_cols]]
            else:
                dico_network["UniProt-AC"][line[2]].append([line[i] for i in network_uniprot_cols])
            dico_GeneID_to_UniProt[line[0]]=line[2]

        r = requests.get("https://reactome.org/download/current/UniProt2Reactome.txt")
        r.encoding ="utf-8"
        tab_file = csv.reader(r.content.splitlines(), delimiter='\t')
        dico_nodes = {}
        uniProt_index=0
        pathway_description_index=3
        species_index=5
        for line in tab_file :
            if line[species_index]==species_dict[species]:
                if line[uniProt_index] in dico_nodes :
                    dico_nodes[line[uniProt_index]].append(line[pathway_description_index])
                else :
                    dico_nodes[line[uniProt_index]] = [line[pathway_description_index]]

        dico={}
        dico['network']=dico_network
        dico['nodes']=dico_nodes
        dico['convert']=dico_GeneID_to_UniProt

    #writing output
    output_file = species+'_'+interactome+'_dict_'+ time.strftime("%d-%m-%Y") + ".json"
    path = os.path.join(target_directory,output_file)
    name = species+" ("+species_dict[species]+") "+time.strftime("%d/%m/%Y")
    id = species+"_"+interactome+"_"+ time.strftime("%d-%m-%Y")

    with open(path, 'w') as handle:
        json.dump(dico, handle, sort_keys=True)

    data_table_entry = dict(id=id, name = name, value = species, path = path)
    _add_data_table_entry(data_manager_dict, data_table_entry, "proteore_"+interactome+"_dictionaries")

39:ec6252ad1a8e

    ##BioGRID
    if interactome=="biogrid":

        tab2_link="https://downloads.thebiogrid.org/Download/BioGRID/Release-Archive/BIOGRID-3.5.167/BIOGRID-ORGANISM-3.5.167.tab2.zip"

        #download zip file
        r = requests.get(tab2_link)
        with open("BioGRID.zip", "wb") as code:
            code.write(r.content)
    
        #unzip files

        file_path="tmp_BioGRID/BIOGRID-ORGANISM-"+species_dict[species].replace(" ","_")+"-3.5.167.tab2.txt"
        with open(file_path,"r") as handle :
            tab_file = csv.reader(handle,delimiter="\t")
            dico_network = {}
            GeneID_index=1
            network_cols=[1,2,7,8,11,12,14,18,20]
            for line in tab_file : 
                if line[GeneID_index] not in dico_network:
                    dico_network[line[GeneID_index]]=[[line[i] for i in network_cols]]
                else:
                    dico_network[line[GeneID_index]].append([line[i] for i in network_cols])

        #delete tmp_BioGRID directory
        os.remove("BioGRID.zip")
        shutil.rmtree("tmp_BioGRID", ignore_errors=True) 
        
        #download NCBI2Reactome.txt file and build dictionary
        with requests.Session() as s:
            r = s.get('https://www.reactome.org/download/current/NCBI2Reactome.txt')
            r.encoding = r.apparent_encoding
            tab_file = csv.reader(r.text.splitlines(), delimiter='\t')

        dico_nodes = {}
        uniProt_index=0
        pathway_description_index=3
        species_index=5
        for line in tab_file :
            if line[species_index]==species_dict[species]:
                if line[uniProt_index] in dico_nodes :
                    dico_nodes[line[uniProt_index]].append(line[pathway_description_index])
                else :
                    dico_nodes[line[uniProt_index]] = [line[pathway_description_index]]

        dico={}
        dico['network']=dico_network
        dico['nodes']=dico_nodes

    ##Bioplex
    elif interactome=="bioplex":

        with requests.Session() as s:
            r = s.get('http://bioplex.hms.harvard.edu/data/BioPlex_interactionList_v4a.tsv')
            r = r.content.decode('utf-8')
            bioplex = csv.reader(r.splitlines(), delimiter='\t')

        dico_network = {}
        dico_network["GeneID"]={}
        network_geneid_cols=[0,1,4,5,8]
        dico_network["UniProt-AC"]={}
        network_uniprot_cols=[2,3,4,5,8]
        dico_GeneID_to_UniProt = {}
        for line in bioplex :
            if line[0] not in dico_network["GeneID"]:
                dico_network["GeneID"][line[0]]=[[line[i] for i in network_geneid_cols]]
            else :
                dico_network["GeneID"][line[0]].append([line[i] for i in network_geneid_cols])

                dico_network["UniProt-AC"][line[2]]=[[line[i] for i in network_uniprot_cols]]
            else:
                dico_network["UniProt-AC"][line[2]].append([line[i] for i in network_uniprot_cols])
            dico_GeneID_to_UniProt[line[0]]=line[2]

        with requests.Session() as s:
            download = s.get('https://reactome.org/download/current/UniProt2Reactome.txt')
            decoded_content = download.content.decode('utf-8')
            tab_file = csv.reader(decoded_content.splitlines(), delimiter='\t')

        dico_nodes_uniprot = {}
        uniProt_index=0
        pathway_description_index=3
        species_index=5
        for line in tab_file :
            if line[species_index]==species_dict[species]:
                if line[uniProt_index] in dico_nodes_uniprot :
                    dico_nodes_uniprot[line[uniProt_index]].append(line[pathway_description_index])
                else :
                    dico_nodes_uniprot[line[uniProt_index]] = [line[pathway_description_index]]

        with requests.Session() as s:
            r = s.get('https://www.reactome.org/download/current/NCBI2Reactome.txt')
            r.encoding = r.apparent_encoding
            tab_file = csv.reader(r.text.splitlines(), delimiter='\t')

        dico_nodes_geneid = {}
        uniProt_index=0
        pathway_description_index=3
        species_index=5
        for line in tab_file :
            if line[species_index]==species_dict[species]:
                if line[uniProt_index] in dico_nodes_geneid :
                    dico_nodes_geneid[line[uniProt_index]].append(line[pathway_description_index])
                else :
                    dico_nodes_geneid[line[uniProt_index]] = [line[pathway_description_index]]

        dico={}
        dico_nodes={}
        dico_nodes['GeneID']=dico_nodes_geneid
        dico_nodes['UniProt-AC']=dico_nodes_uniprot
        dico['network']=dico_network
        dico['nodes']=dico_nodes
        dico['convert']=dico_GeneID_to_UniProt

    #writing output
    output_file = species+'_'+interactome+'_dict_'+ time.strftime("%d-%m-%Y") + ".json"
    path = os.path.join(target_directory,output_file)
    name = species+" ("+species_dict[species]+") "+time.strftime("%d/%m/%Y")
    id = species+"_"+interactome+"_"+ time.strftime("%d-%m-%Y")

    with open(path, 'w', encoding="utf-8") as handle:
        json.dump(dico, handle, sort_keys=True)

    data_table_entry = dict(id=id, name = name, value = species, path = path)
    _add_data_table_entry(data_manager_dict, data_table_entry, "proteore_"+interactome+"_dictionaries")