#!/usr/bin/env python# Dénes Türei EMBL 2017# turei.denes@gmail.comimportpypathfrompypathimportdata_formatsasdf# initializing a PyPath object and loading a sample networkpa=pypath.PyPath()pa.load_resources({'signor':df.pathway['signor']})# here we download data from one tissue (BTO:0000661)# ProteomicsDB is huge, downloading all tissues would# take maybe one hour# to access ProteomicsDB data, you need to register on# their webpage and write an email requesting access# to the API; once they grant access you can use your# user and password here:pa.get_proteomicsdb(user='myusername',passwd='mypassword',tissues=['BTO:0000661'])# here we can see all available tissues and samples# in ProteomicsDB:pa.proteomicsdb.samples# loading the expression values (FPKMs) into a vertex attribute:pa.prdb_tissue_expr(tissue='BTO:0000661')# filter the network by deleting all proteins not detected in Jurkat cells:jurkat_cell_network=pa.tissue_network('BTO:0000661')# loading all data from Human Protein Atlaspa.load_hpa()# attributes with tissue names have been created:pa.graph.vs.attribute_names()# filter the network by simply deleting all proteins# having 0 value for urothelial cells:urothelium_network=pa.tissue_network('urinary bladder:urothelial cells')
Comments (0)
HTTPSSSH
You can clone a snippet to your computer for local editing.
Learn more.