CyJS Assembler

Assemble a network from text using existing INDRA functionality
Translate this into a model supported by cytoscape.js
Visualize standalone, or within notebook

I. Describe your network in plain English

We have described the interactions in the McCormick RAS pathway map using plain English.
Let's load this set of sentences.



In [1]:

    
from __future__ import absolute_import, print_function, unicode_literals
from builtins import dict, str
statement_path = 'ras_pathway.txt'
txt = open(statement_path, 'rt').read()
print(txt)









    



Growth-factor proteins activate EGFR, ERBB2 and FGFR.
Growth-factor proteins activate PDGFR.
Growth-factor proteins activate MET, ROS1 and ALK.
EGFR, ERBB2, PDGFR, MET, ROS1, ALK and FGFR activate GRB2 and SHC.
GRB2 and SHC activate RASGRF and SOS.
GRB2 binds SHC.
SOS and RASGRF activate HRAS, NRAS and KRAS.
RASGRP activates HRAS, KRAS and NRAS.
SPRY deactivates HRAS, KRAS and NRAS.
RASA/ARHGAP35 deactivates HRAS, NRAS and KRAS.
RASAL deactivates HRAS, NRAS and KRAS.
NF1/SPRED deactivates HRAS, NRAS and KRAS.
RASA/ARHGAP35 deactivates RHOA, RHOB and RHOC.
RASAL deactivates RHOA, RHOB and RHOC.
NF1/SPRED deactivates RHOA, RHOB and RHOC.
HRAS, NRAS and KRAS activate RALGDS.
RALGDS activates RALA and RALB.
HRAS, NRAS and KRAS activate ARAF, BRAF and RAF1.
ARAF, BRAF and RAF1 activate MAP2K1 and MAP2K2.
MAP2K1 and MAP2K2 activate MAPK1 and MAPK3.
MAPK1 and MAPK3 activate ETS, JUN and FOS.
KSR binds ARAF, BRAF and RAF1.
KSR binds MAP2K1 and MAP2K2.
KSR binds MAPK1 and MAPK3.
ETS, FOS and JUN activate MDM2, CCND1 and DUSP.
MDM2 deactivates TP53.
CCND1 activates CDK4 and CDK6, which deactivate RB1.
DUSP deactivates MAPK1 and MAPK3.
SOS and RASGRF activate RHOA, RHOB and RHOC.
RHOA, RHOB and RHOC activate ROCK1 and ROCK2.
HRAS, NRAS and KRAS activate PIK3C and PIK3R.
PIK3C and PIK3R activate PIP3.
PTEN deactivates PIP3.
PIP3 activates PDPK1, AKT and TIAM.
PDPK1 activates AKT.
AKT deactivates TSC1/TSC2.
TSC1/TSC2 deactivates RHEB.
RHEB activates mTORC2.
STK11 activates PRKAA, PRKAB and PRKAG.
PRKAA, PRKAB and PRKAG deactivate mTORC2.
mTORC2 deactivates EIF4EBP1.
mTORC2 activates RPS6KA.
TIAM activates RAC, which activates PAK.

II. Process text into INDRA statements using REACH parser

If we have never parsed this text before (or we've made changes to it) we should process it with REACH
This will yield a set of INDRA statements
We will then pickle the statements so we don't have to parse them every time we run this script.
- Change the cell below to from Code -> Raw NBConvert in order to not execute it every time



In [2]:

    
from indra import reach
rp = reach.process_text(txt, offline=False)
st = rp.statements



In [3]:

    
from indra.preassembler.grounding_mapper import GroundingMapper, gm

GM = GroundingMapper(gm)
mapped_stmts = GM.map_agents(st, do_rename=True)

import pickle
pickle.dump(mapped_stmts, open("st.pkl", "wb"))

III. Assemble an INDRA model



In [4]:

    
import pickle
st = pickle.load(open("st.pkl", "rb"))

What do the statements look like?

Let's see.



In [5]:

    
st









    Out[5]:





[Complex(GRB2(), SHC()),
 Complex(KSR(), RAF1()),
 Complex(KSR(), BRAF()),
 Complex(KSR(), ARAF()),
 Complex(KSR(), MAP2K1()),
 Complex(KSR(), MAP2K2()),
 Complex(KSR(), MAPK3()),
 Complex(KSR(), MAPK1()),
 Activation(Growth_factor_proteins(), activity, ERBB2(), activity, True),
 Activation(Growth_factor_proteins(), activity, FGFR(), activity, True),
 Activation(Growth_factor_proteins(), activity, EGFR(), activity, True),
 Activation(Growth_factor_proteins(), activity, PDGFR(), activity, True),
 Activation(Growth_factor_proteins(), activity, ALK(), activity, True),
 Activation(Growth_factor_proteins(), activity, ROS1(), activity, True),
 Activation(PDGFR(), activity, GRB2(), activity, True),
 Activation(ERBB2(), activity, GRB2(), activity, True),
 Activation(ALK(), activity, SHC(), activity, True),
 Activation(PDGFR(), activity, SHC(), activity, True),
 Activation(FGFR(), activity, GRB2(), activity, True),
 Activation(ALK(), activity, GRB2(), activity, True),
 Activation(ROS1(), activity, SHC(), activity, True),
 Activation(ERBB2(), activity, SHC(), activity, True),
 Activation(ROS1(), activity, GRB2(), activity, True),
 Activation(FGFR(), activity, SHC(), activity, True),
 Activation(EGFR(), activity, GRB2(), activity, True),
 Activation(EGFR(), activity, SHC(), activity, True),
 Activation(SHC(), activity, RASGRF(), activity, True),
 Activation(SHC(), activity, SOS(), activity, True),
 Activation(GRB2(), activity, SOS(), activity, True),
 Activation(GRB2(), activity, RASGRF(), activity, True),
 Activation(RASGRF(), activity, KRAS(), activity, True),
 Activation(RASGRF(), activity, NRAS(), activity, True),
 Activation(SOS(), activity, HRAS(), activity, True),
 Activation(SOS(), activity, KRAS(), activity, True),
 Activation(SOS(), activity, NRAS(), activity, True),
 Activation(RASGRF(), activity, HRAS(), activity, True),
 Activation(RASGRP(), activity, KRAS(), activity, True),
 Activation(RASGRP(), activity, NRAS(), activity, True),
 Activation(RASGRP(), activity, HRAS(), activity, True),
 Activation(SPRY(), activity, NRAS(), activity, False),
 Activation(SPRY(), activity, KRAS(), activity, False),
 Activation(SPRY(), activity, HRAS(), activity, False),
 Activation(RASA(), activity, KRAS(), activity, False),
 Activation(ARHGAP35(), activity, KRAS(), activity, False),
 Activation(ARHGAP35(), activity, HRAS(), activity, False),
 Activation(ARHGAP35(), activity, NRAS(), activity, False),
 Activation(RASA(), activity, NRAS(), activity, False),
 Activation(RASA(), activity, HRAS(), activity, False),
 Activation(RASAL(), activity, HRAS(), activity, False),
 Activation(RASAL(), activity, KRAS(), activity, False),
 Activation(RASAL(), activity, NRAS(), activity, False),
 Activation(NF1(), activity, KRAS(), activity, False),
 Activation(NF1(), activity, HRAS(), activity, False),
 Activation(NF1(), activity, NRAS(), activity, False),
 Activation(SPRED(), activity, NRAS(), activity, False),
 Activation(SPRED(), activity, HRAS(), activity, False),
 Activation(SPRED(), activity, KRAS(), activity, False),
 Activation(ARHGAP35(), activity, RHOA(), activity, False),
 Activation(RASA(), activity, RHOC(), activity, False),
 Activation(RASA(), activity, RHOB(), activity, False),
 Activation(ARHGAP35(), activity, RHOC(), activity, False),
 Activation(RASA(), activity, RHOA(), activity, False),
 Activation(ARHGAP35(), activity, RHOB(), activity, False),
 Activation(RASAL(), activity, RHOB(), activity, False),
 Activation(RASAL(), activity, RHOC(), activity, False),
 Activation(RASAL(), activity, RHOA(), activity, False),
 Activation(SPRED(), activity, RHOA(), activity, False),
 Activation(NF1(), activity, RHOB(), activity, False),
 Activation(NF1(), activity, RHOA(), activity, False),
 Activation(NF1(), activity, RHOC(), activity, False),
 Activation(SPRED(), activity, RHOB(), activity, False),
 Activation(SPRED(), activity, RHOC(), activity, False),
 Activation(KRAS(), activity, RALGDS(), activity, True),
 Activation(NRAS(), activity, RALGDS(), activity, True),
 Activation(HRAS(), activity, RALGDS(), activity, True),
 Activation(RALGDS(), activity, RALA(), activity, True),
 Activation(RALGDS(), activity, RALB(), activity, True),
 Activation(KRAS(), activity, RAF1(), activity, True),
 Activation(KRAS(), activity, BRAF(), activity, True),
 Activation(KRAS(), activity, ARAF(), activity, True),
 Activation(HRAS(), activity, RAF1(), activity, True),
 Activation(NRAS(), activity, RAF1(), activity, True),
 Activation(HRAS(), activity, BRAF(), activity, True),
 Activation(NRAS(), activity, ARAF(), activity, True),
 Activation(HRAS(), activity, ARAF(), activity, True),
 Activation(NRAS(), activity, BRAF(), activity, True),
 Activation(BRAF(), activity, MAP2K1(), activity, True),
 Activation(RAF1(), activity, MAP2K2(), activity, True),
 Activation(ARAF(), activity, MAP2K2(), activity, True),
 Activation(ARAF(), activity, MAP2K1(), activity, True),
 Activation(RAF1(), activity, MAP2K1(), activity, True),
 Activation(BRAF(), activity, MAP2K2(), activity, True),
 Activation(MAP2K2(), activity, MAPK1(), activity, True),
 Activation(MAP2K1(), activity, MAPK1(), activity, True),
 Activation(MAP2K1(), activity, MAPK3(), activity, True),
 Activation(MAP2K2(), activity, MAPK3(), activity, True),
 Activation(MAPK1(), activity, FOS_family(), activity, True),
 Activation(MAPK3(), activity, FOS_family(), activity, True),
 Activation(MAPK1(), activity, JUN_family(), activity, True),
 Activation(MAPK1(), activity, ETS(), activity, True),
 Activation(MAPK3(), activity, JUN_family(), activity, True),
 Activation(MAPK3(), activity, ETS(), activity, True),
 Activation(ETS(), activity, DUSP(), activity, True),
 Activation(JUN_family(), activity, MDM2(), activity, True),
 Activation(FOS_family(), activity, DUSP(), activity, True),
 Activation(ETS(), activity, CCND1(), activity, True),
 Activation(FOS_family(), activity, CCND1(), activity, True),
 Activation(JUN_family(), activity, CCND1(), activity, True),
 Activation(ETS(), activity, MDM2(), activity, True),
 Activation(JUN_family(), activity, DUSP(), activity, True),
 Activation(FOS_family(), activity, MDM2(), activity, True),
 Activation(MDM2(), activity, TP53(), activity, False),
 Activation(CDK6(), activity, RB1(), activity, False),
 Activation(CCND1(), activity, CDK6(), activity, True),
 Activation(CDK4(), activity, RB1(), activity, False),
 Activation(CCND1(), activity, CDK4(), activity, True),
 Activation(DUSP(), activity, MAPK3(), activity, False),
 Activation(DUSP(), activity, MAPK1(), activity, False),
 Activation(SOS(), activity, RHOA(), activity, True),
 Activation(RASGRF(), activity, RHOB(), activity, True),
 Activation(RASGRF(), activity, RHOC(), activity, True),
 Activation(RASGRF(), activity, RHOA(), activity, True),
 Activation(SOS(), activity, RHOC(), activity, True),
 Activation(SOS(), activity, RHOB(), activity, True),
 Activation(RHOB(), activity, ROCK1(), activity, True),
 Activation(RHOC(), activity, ROCK2(), activity, True),
 Activation(RHOA(), activity, ROCK2(), activity, True),
 Activation(RHOC(), activity, ROCK1(), activity, True),
 Activation(RHOB(), activity, ROCK2(), activity, True),
 Activation(RHOA(), activity, ROCK1(), activity, True),
 Activation(NRAS(), activity, PIK3R_I(), activity, True),
 Activation(HRAS(), activity, PI3K_p110(), activity, True),
 Activation(KRAS(), activity, PIK3R_I(), activity, True),
 Activation(NRAS(), activity, PI3K_p110(), activity, True),
 Activation(HRAS(), activity, PIK3R_I(), activity, True),
 Activation(KRAS(), activity, PI3K_p110(), activity, True),
 Activation(PIK3R_I(), activity, PIP3(), activity, True),
 Activation(PI3K_p110(), activity, PIP3(), activity, True),
 Activation(PTEN(), activity, PIP3(), activity, False),
 Activation(PIP3(), activity, TIAM(), activity, True),
 Activation(PIP3(), activity, PDPK1(), activity, True),
 Activation(PIP3(), activity, AKT(), activity, True),
 Activation(PDPK1(), activity, AKT(), activity, True),
 Activation(AKT(), activity, TSC1(), activity, False),
 Activation(AKT(), activity, TSC2(), activity, False),
 Activation(TSC2(), activity, RHEB(), activity, False),
 Activation(TSC1(), activity, RHEB(), activity, False),
 Activation(RHEB(), activity, mTORC2(), activity, True),
 Activation(STK11(), activity, AMPK_beta(), activity, True),
 Activation(STK11(), activity, AMPK_alpha(), activity, True),
 Activation(STK11(), activity, AMPK_gamma(), activity, True),
 Activation(AMPK_beta(), activity, mTORC2(), activity, False),
 Activation(AMPK_alpha(), activity, mTORC2(), activity, False),
 Activation(AMPK_gamma(), activity, mTORC2(), activity, False),
 Activation(mTORC2(), activity, EIF4EBP1(), activity, False),
 Activation(mTORC2(), activity, P90RSK(), activity, True),
 Activation(RAC(), activity, PAK(), activity, True),
 Activation(TIAM(), activity, RAC(), activity, True)]

Import some necessities

these let us work with INDRA statements and the CyJSAssembler



In [6]:

    
from indra.statements import *
from indra.assemblers import CyJSAssembler

Instntiate a CyJSAssembler



In [7]:

    
cja = CyJSAssembler()

add the statements into the assembler



In [8]:

    
cja.add_statements(st)

make_model

grouping will combine structurally identical nodes under a group node
virtual edges are the edges that belong to grouped nodes. They are not visualized but should be maintained for our default layout
add_edge_weights weighs the edges of nodes depending on how many members they have. Again, this is used in our default layout.



In [9]:

    
cja.make_model(grouping=True, 
               drop_virtual_edges=False,
               add_edge_weights=True)









    Out[9]:





'{\n "mut_colorscale_str": "[]", \n "model_elements_str": "{\\n \\"edges\\": [\\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 0, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 1, \\n    \\"target\\": 2, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 3, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 1, \\n    \\"target\\": 4, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 5, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 6, \\n    \\"target\\": 7, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 8, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 6, \\n    \\"target\\": 9, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 10, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 11, \\n    \\"target\\": 12, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 13, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 14, \\n    \\"target\\": 12, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 15, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 16, \\n    \\"target\\": 12, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 17, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 18, \\n    \\"target\\": 19, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 20, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 18, \\n    \\"target\\": 21, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 22, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 23, \\n    \\"target\\": 24, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 25, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 23, \\n    \\"target\\": 26, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 27, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 23, \\n    \\"target\\": 28, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 29, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 23, \\n    \\"target\\": 30, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 31, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 23, \\n    \\"target\\": 32, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 33, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 23, \\n    \\"target\\": 34, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 35, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 36, \\n    \\"target\\": 19, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 37, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 36, \\n    \\"target\\": 21, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 38, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 39, \\n    \\"target\\": 40, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 41, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 39, \\n    \\"target\\": 42, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 43, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 40, \\n    \\"target\\": 44, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 45, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 42, \\n    \\"target\\": 44, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 46, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 47, \\n    \\"target\\": 48, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 49, \\n    \\"polarity\\": \\"negative\\", \\n    \\"source\\": 47, \\n    \\"target\\": 50, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 51, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 52, \\n    \\"target\\": 7, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 53, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 52, \\n    \\"target\\": 9, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 54, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 55, \\n    \\"target\\": 7, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 56, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 55, \\n    \\"target\\": 9, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 57, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 58, \\n    \\"target\\": 39, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 59, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 58, \\n    \\"target\\": 47, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 60, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 58, \\n    \\"target\\": 61, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 62, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 63, \\n    \\"target\\": 7, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 64, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 63, \\n    \\"target\\": 9, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 65, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 66, \\n    \\"target\\": 39, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   \\"data\\": {\\n    \\"i\\": \\"Virtual\\", \\n    \\"id\\": 67, \\n    \\"polarity\\": \\"positive\\", \\n    \\"source\\": 66, \\n    \\"target\\": 47, \\n    \\"weight\\": 1\\n   }\\n  }, \\n  {\\n   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set_context

We integrate gene expression and mutation status into our visualization
- Gene expression is log10 transformed and displayed by color intensity on an n_bins scale
- Mutational status is represented by green (wt) and orange (mutated)
Here, we chose the LOXIMVI_SKIN melanoma cell line from CCLE



In [10]:

    
cja.set_context(cell_type = 'LOXIMVI_SKIN', 
                bin_expression = True, 
                n_bins = 9)

save_model

We save the model as 'model.js' which is the file expected by our visualizer
must be saved in cyjs folder where the html and js files for the visualization reside



In [11]:

    
cja.save_model('cyjs/model.js')

Display the assembled model



In [13]:

    
%%html
<iframe width="100%" height="600" src="cyjs/index.html"></iframe>



In [ ]: