def create_test_model(test_network_file = humannet_filename): """Returns a nampy model for testing. test_network_file: a two-column network file to be read """ # from os import name as __name from nampy.networkio import networkio the_nampy_model = networkio.create_network_model_from_textfile('humannet', test_network_file, verbose = False) return the_nampy_model
# protein complexes that facilitate viral infection. PLOS ONE, 9(5), e96687. import nampy from nampy.networkio import networkio from nampy.annotation import idmapping from nampy.manipulation import manipulation from nampy.monopartiteanalysis import prince # Let's work with a version of HumanNet # Lee, I., Blom, U. M., Wang, P. I., Shim, J. E., & Marcotte, E. M. (2011). # Prioritizing candidate disease genes by network-based boosting of genome-wide association data. # Genome research, 21(7), 1109–21. doi:10.1101/gr.118992.110 data_dir = nampy.__path__[0] + '/data/' network_file = data_dir + "HumanNet_v1_join_networkonly.txt" humannet = networkio.create_network_model_from_textfile('humannet', network_file, verbose = True) # Add ids courtesy of bioservices # note you may need to "easy_install bioservices" first # also, you may want to add email = '*****@*****.**' # so ncbi can contact you if there are issues with the query # Note there may some errors returned while querying but # each query is generally successful within the three tries. humannet = idmapping.get_more_node_ids(humannet, node_id_type = "Entrez Gene (GeneID)", mapping_types = ['Entrez Gene (GeneID)', "UniProtKB ACC", 'UniProtKB ID', 'Symbol'], verbose = True) # APMS host targets from # Jäger, S., Cimermancic, P., Gulbahce, N., Johnson, J. R., McGovern, K. E., Clarke, S. C., # … Krogan, N. J. (2012). Global landscape of HIV-human protein complexes. # Nature, 481(7381), 365–70. doi:10.1038/nature10719 hiv_apms_file = data_dir + "published_hiv_apms_factors.txt" apms_source = networkio.create_source_dict_from_textfile(hiv_apms_file)