In [30]:

    

import pandas
df = pandas.read_csv("shared/pathway_commons.sif", 
                     sep="\t", 
                     names=["species1","interaction_type","species2"])


    

In [4]:

    

interaction_types_ppi = set(["interacts-with",
                           "in-complex-with",
                           "neighbor-of"])

interaction_types_metab = set(["controls-production-of",
                             "consumption-controlled-by",
                             "controls-production-of",
                             "controls-transport-of-chemical"])

interaction_types_ppd = set(["catalysis-precedes",
                           "controls-phosphorylation-of",
                           "controls-state-change-of",
                           "controls-transport-of",
                           "controls-expression-of"])


    

In [38]:

    

ppirows = df.interaction_type.isin(interaction_types_ppi)
metabrows = df.interaction_type.isin(interaction_types_metab)
ppdrows = df.interaction_type.isin(interaction_types_ppd)

df_ppi = df[df.interaction_type.isin(interaction_types_ppi)]
df_metab = df[df.interaction_type.isin(interaction_types_metab)]
df_ppd = df[df.interaction_type.isin(interaction_types_ppd)]

df_ppi_el = df_ppi[["species1","species2"]].values.tolist()
df_metab_el = df_metab[["species1","species2"]].values.tolist()
df_ppd_el = df_ppd[["species1","species2"]].values.tolist()


    

In [45]:

    

from igraph import Graph
from igraph import summary

graph_ppi = Graph.TupleList(df_ppi_el)
summary(graph_ppi)


    

    




IGRAPH UN-- 17020 523498 -- 
+ attr: name (v)

In [47]:

    

graph_metab = Graph.TupleList(df_metab_el, directed=True)
summary(graph_metab)


    

    




IGRAPH DN-- 7620 38145 -- 
+ attr: name (v)

In [48]:

    

graph_ppd = Graph.TupleList(df_ppd_el, directed=True)
summary(graph_ppd)


    

    




IGRAPH DN-- 16063 359713 -- 
+ attr: name (v)

In [51]:

    

type(df_ppi_el)


    

    
Out[51]:





list

In [ ]: