Cytoscape CX2 export¶

CX2 is useful when a graph should be inspected in Cytoscape. AnnNet can choose how hyperedges are projected for tools that do not support them directly.

In [1]:

import annnet as an

an.info()

import annnet as an an.info()

Out[1]:

annnetv0.2.0·graph: networkx·plot: graphviz·I/O: 12/13

Show environment details

Version	v0.2.0
License	BSD-3-Clause
Authors	Youssef Zerta ✉, Daniele Bottazzi ✉, Denes Turei ✉
Repository	https://github.com/saezlab/annnet
Documentation	https://saezlab.github.io/annnet/reference/
Default adapter backend	networkx
Default plot backend	graphviz
Graph backends	✓networkx✓igraph✗graph-tool✓pyg
Plot backends	✓graphviz✗pydot✓matplotlib
Tabular data backends	✓polars✓pandas✓pyarrow
I/O modules	✓annnet✓json/ndjson✓dataframes✓csv✓excel✓graphml/gexf✓sif✓cx2✓parquet✓zarr✗sbml✓scverse✓omnipath
Installable bundles	backendsplotiostorageall

Build a graph with a hyperedge¶

In [2]:

G = an.AnnNet(directed=True)
G.add_vertices(['A', 'B', 'C', 'D', 'E'])
G.add_edges('A', 'B', edge_id='binary_edge', weight=1.0)
G.add_edges('A', 'B', edge_id='parallel_edge', weight=0.65)
G.add_edges('B', 'C', edge_id='complex_edge', directed=False, weight=0.8)
G.add_edges(src=['B', 'C'], tgt=['D', 'E'], edge_id='reaction', directed=True, weight=2.0)
G.attrs.set_vertex_attrs_bulk(
    {
        'A': {'label': 'ligand'},
        'B': {'label': 'enzyme'},
        'C': {'label': 'cofactor'},
        'D': {'label': 'product'},
        'E': {'label': 'byproduct'},
    }
)

G.views.edges().select(['edge_id', 'kind', 'source', 'target', 'head', 'tail'])

G = an.AnnNet(directed=True) G.add_vertices(['A', 'B', 'C', 'D', 'E']) G.add_edges('A', 'B', edge_id='binary_edge', weight=1.0) G.add_edges('A', 'B', edge_id='parallel_edge', weight=0.65) G.add_edges('B', 'C', edge_id='complex_edge', directed=False, weight=0.8) G.add_edges(src=['B', 'C'], tgt=['D', 'E'], edge_id='reaction', directed=True, weight=2.0) G.attrs.set_vertex_attrs_bulk( { 'A': {'label': 'ligand'}, 'B': {'label': 'enzyme'}, 'C': {'label': 'cofactor'}, 'D': {'label': 'product'}, 'E': {'label': 'byproduct'}, } ) G.views.edges().select(['edge_id', 'kind', 'source', 'target', 'head', 'tail'])

Out[2]:

shape: (4, 6)

edge_id	kind	source	target	head	tail
str	str	str	str	list[str]	list[str]
"binary_edge"	"binary"	"A"	"B"	null	null
"parallel_edge"	"binary"	"A"	"B"	null	null
"complex_edge"	"binary"	"B"	"C"	null	null
"reaction"	"hyper"	"B|C"	"D|E"	["B", "C"]	["D", "E"]

Preview the network¶

The CX2 file is for Cytoscape. For static documentation, a Graphviz preview gives a lightweight embedded view of the same topology.

In [3]:

from annnet.utils import plotting

plotting.plot(G, backend='graphviz', show_edge_labels=True)

from annnet.utils import plotting plotting.plot(G, backend='graphviz', show_edge_labels=True)

Out[3]:

Compare hyperedge export modes¶

In [4]:

for mode in ['skip', 'expand', 'reify']:
    cx2 = an.to_cx2(G, hyperedges=mode, export_name=f'annnet-{mode}')
    edge_aspect = next(item['edges'] for item in cx2 if 'edges' in item)
    node_aspect = next(item['nodes'] for item in cx2 if 'nodes' in item)
    print(mode, 'nodes:', len(node_aspect), 'edges:', len(edge_aspect))

for mode in ['skip', 'expand', 'reify']: cx2 = an.to_cx2(G, hyperedges=mode, export_name=f'annnet-{mode}') edge_aspect = next(item['edges'] for item in cx2 if 'edges' in item) node_aspect = next(item['nodes'] for item in cx2 if 'nodes' in item) print(mode, 'nodes:', len(node_aspect), 'edges:', len(edge_aspect))

skip nodes: 5 edges: 3
expand nodes: 5 edges: 7
reify nodes: 6 edges: 7

Round-trip through the CX2 manifest¶

In [5]:

import json

cx2 = an.to_cx2(G, hyperedges='reify', export_name='annnet-reified')
restored = an.from_cx2(cx2)

print('restored shape:', restored.shape)
print('restored hyperedges:', sorted(restored.hyperedge_definitions))
print(json.dumps(cx2[:3], indent=2))

import json cx2 = an.to_cx2(G, hyperedges='reify', export_name='annnet-reified') restored = an.from_cx2(cx2) print('restored shape:', restored.shape) print('restored hyperedges:', sorted(restored.hyperedge_definitions)) print(json.dumps(cx2[:3], indent=2))

restored shape: (5, 4)
restored hyperedges: ['reaction']
[
  {
    "CXVersion": "2.0",
    "hasFragments": false
  },
  {
    "metaData": [
      {
        "name": "attributeDeclarations",
        "elementCount": 1
      },
      {
        "name": "networkAttributes",
        "elementCount": 1
      },
      {
        "name": "nodes",
        "elementCount": 6
      },
      {
        "name": "edges",
        "elementCount": 7
      }
    ]
  },
  {
    "attributeDeclarations": [
      {
        "nodes": {
          "label": {
            "d": "string"
          },
          "name": {
            "d": "string"
          },
          "is_hyperedge": {
            "d": "boolean"
          },
          "eid": {
            "d": "string"
          },
          "tag": {
            "d": "string"
          },
          "reaction": {
            "d": "string"
          }
        },
        "edges": {
          "interaction": {
            "d": "string"
          },
          "weight": {
            "d": "double"
          },
          "edge_id": {
            "d": "string"
          },
          "role": {
            "d": "string"
          }
        },
        "networkAttributes": {
          "__AnnNet_Manifest__": {
            "d": "string"
          },
          "name": {
            "d": "string"
          },
          "directed": {
            "d": "boolean"
          }
        }
      }
    ]
  }
]

skip, expand, and reify are explicit choices about what Cytoscape should see. A true embedded Cytoscape.js widget would need an additional browser asset; this notebook keeps the docs static by showing the CX2 payload plus a Graphviz preview.