Usage

This notebook provides the steps to build a network starting from a list of genes, and using the default functionalities of Omniflow.

[2]:

%%time
from neko.core.network import Network
from neko._visual.visualize_network import NetworkVisualizer
from neko._inputs.resources import Resources
from neko._annotations.gene_ontology import Ontology
import omnipath as op

CPU times: user 1.85 s, sys: 357 ms, total: 2.21 s
Wall time: 2.15 s

1. Define the list of genes of interest

[3]:

genes = ["SRC", "NOTCH1", "FAK", "CDH1", "CDH2", "VIM", "MAP4K4", "LATS1", "LATS2", "PTK2B"]

2. Create a network using as input the gene set.

Note

NB! If no resource is specified, the default used resource by the package is omnipath.all_interactions(). To add new resources, please see the Add resources tutorial.

2A. Import genes as network nodes

[4]:

new_net1 = Network(genes)

[5]:

#Print node dataframe
new_net1.nodes

[5]:

	Genesymbol	Uniprot	Type
0	SRC	P12931	NaN
1	NOTCH1	P46531	NaN
2	PTK2	Q05397	NaN
3	CDH1	P12830	NaN
4	CDH2	P19022	NaN
5	VIM	P08670	NaN
6	MAP4K4	O95819	NaN
7	LATS1	O95835	NaN
8	LATS2	Q9NRM7	NaN
9	PTK2B	Q14289	NaN

2B. Explore if the nodes are connected without introducing new intermidiate nodes

[6]:

%%time
new_net1.connect_nodes(only_signed=True, consensus_only=True)

CPU times: user 889 ms, sys: 0 ns, total: 889 ms
Wall time: 888 ms

2C. Visualize the network with the following command.

The network picture is also exported in the working repository, in pdf format.

[7]:

visualizer = NetworkVisualizer(new_net1, color_by='effect')
visualizer.render()

../_images/notebooks_1_network_building_11_0.svg

2D. Connect disconnected nodes by importing intermediate nodes.

The parameter maxlen is used to verify that in the network all the nodes have a distance < than maxlen.

The parameter only_signed forces the algorithm to look for just signed interactions.

The parameter consensus retrieves those interactions with a sign consensus between the references.

The parameter connect_node_when_first_introduced, changes the base algorithm, making it look for possible connection between all the disconnected node in the network when a new bridge-gene is introduced in the network.

[8]:

%%time
new_net1.complete_connection(maxlen=6, k_mean="tight", only_signed=True, connect_node_when_first_introduced=True, consensus=False)

Found a path!
Found a path!
Found a path!
Found a path!
Found a path!
Found a path!
Found a path!
Found a path!
Found a path!
Found a path!
Found a path!
CPU times: user 3min 27s, sys: 98.8 ms, total: 3min 27s
Wall time: 3min 27s

3. Visualize final network

[11]:

#Visualize a specific nodes and
visualizer1 = NetworkVisualizer(new_net1,color_by='effect')
visualizer1.render(output_file='network2')

../_images/notebooks_1_network_building_15_0.svg

[10]:

#Visualize a specific nodes and
visualizer1 = NetworkVisualizer(new_net1, predefined_node = "SRC",color_by='effect')
visualizer1.render(output_file='network2')

../_images/notebooks_1_network_building_16_0.svg

[10]:

#We can access to the edges of the network
new_net1.edges

[10]:

	source	target	Type	Effect	References
6821	P12931	Q05397	None	stimulation	Adhesome:10085298;Adhesome:10592173;Adhesome:1...
32968	P12931	P19022	None	inhibition	ACSN:15782139;ACSN:16371504;ACSN:16492141;ACSN...
5154	P12931	Q14289	None	stimulation	Adhesome:10329689;Adhesome:10521452;Adhesome:1...
44795	Q14289	Q05397	None	stimulation	Adhesome:16760434;HPRD:16760434;KEA:12960434;K...
11582	P12931	P35222	None	stimulation	ACSN:10593980;ACSN:12123611;ACSN:15782139;ACSN...
...	...	...	...	...	...
67482	P00533	Q05397	None	stimulation	ACSN:10545505;ACSN:16919435;ACSN:17496910;ACSN...
7631	Q14289	P00533	None	stimulation	CA1:11274221;HPRD:10777553;InnateDB:14963038;S...
73973	P00533	P35222	None	stimulation	ACSN:12040186;ACSN:14585353;ACSN:17496910;ACSN...
2907	Q15139	P00533	None	stimulation	CancerCellMap:10523301;CancerCellMap:2984676;C...
78053	P00533	P56945	None	inhibition	KEA:17570479;ProtMapper:15951569;SPIKE_LC:1714...

71 rows × 5 columns