Custom Graphics and Labels

by Kozo Nishida, Kristina Hanspers, Alexander Pico, Barry Demchak

py4cytoscape 0.0.11

This notebook illustrates how Cytoscape’s Custom Graphics can be used to add graphs, charts and other graphics to node, and how to combine Custom Graphics with the enhancedGraphics app for specialized visualizations.

Prerequisites

In addition to this package (py4cytoscape), you will need:

• Cytoscape 3.8 or greater, which can be downloaded from https://cytoscape.org/download.html. Simply follow the installation instructions on screen.

• Complete installation wizard

• Launch Cytoscape

• If your Cytoscape is 3.8.2 or earlier, install FileTransfer App (Follow here to do it.)

NOTE: To run this notebook, you must manually start Cytoscape first – don’t proceed until you have started Cytoscape.

Setup required only in a remote notebook environment

If you’re using a remote Jupyter Notebook environment such as Google Colab, run the cell below. (If you’re running a local Jupyter Notebook server on the desktop machine same with Cytoscape, you don’t need to do that.)

_PY4CYTOSCAPE = 'git+https://github.com/cytoscape/py4cytoscape@0.0.11'
import requests
exec(requests.get("https://raw.githubusercontent.com/cytoscape/jupyter-bridge/master/client/p4c_init.py").text)
IPython.display.Javascript(_PY4CYTOSCAPE_BROWSER_CLIENT_JS) # Start browser client

Note that to use the current py4cytoscape release (instead of v0.0.11), remove the _PY4CYTOSCAPE= line in the snippet above.

Sanity test to verify Cytoscape connection

By now, the connection to Cytoscape should be up and available. To verify this, try a simple operation that doesn’t alter the state of Cytoscape.

import py4cytoscape as p4c
p4c.cytoscape_ping()
p4c.cytoscape_version_info()

You are connected to Cytoscape!

{'apiVersion': 'v1',
 'cytoscapeVersion': '3.8.2',
 'automationAPIVersion': '1.2.0',
 'py4cytoscapeVersion': '0.0.11'}

Open Sample

For this tutorial, we will be using the galFiltered sample session file, which includes a yeast network and associated data.

p4c.open_session()

Opening sampleData/sessions/Yeast Perturbation.cys...

{}

p4c.notebook_export_show_image()

Set style and node color

First, lets change the style to a simple default and the color of nodes to grey:

p4c.set_visual_style('default')
p4c.set_node_color_default('#D8D8D8')

style_name not specified, so updating "default" style.

''

p4c.notebook_export_show_image()

Custom Graphics

Bar chart

In this example, we will create a bar chart with the three expression values, gal1RGexp, gal4RGexp and gal80Rexp, available as attributes in the session file.

Create the Custom Graphic:

p4c.set_node_custom_bar_chart(["gal1RGexp","gal4RGexp","gal80Rexp"])

style_name not specified, so updating "default" style.

''

p4c.notebook_export_show_image()

There are 4 types of Bar Charts and customizable parameters for colors, size, spacing and orientation.

Position the Bar Chart just below the node. This is an optional step that we are doing here just to make room for subsequent graphics. By specifying both anchors at opposite ends, we can get a lot of space between the node and the graphic.

p4c.set_node_custom_position(node_anchor="S", graphic_anchor="N")

style_name not specified, so updating "default" style.

''

p4c.notebook_export_show_image()

Stripes

Next we are going to create stripes of gradient mappings using a horizontal “heatmap”” of the same three data columns and position the heatmap right above the node. For this vignette, we need to also specify the slot number to avoid overwriting the Bar Chart:

p4c.set_node_custom_heat_map_chart(["gal1RGexp","gal4RGexp","gal80Rexp"], slot=2)
p4c.set_node_custom_position(node_anchor="N", graphic_anchor="S", slot=2)

style_name not specified, so updating "default" style.
style_name not specified, so updating "default" style.

''

p4c.notebook_export_show_image()

Pie chart

Finally, we will create a pie chart with two columns, Radiality and Degree, and place it to the left of the node. Here we’ll use the xOffset parameter to be even more specific about where we want to place the graphic relative to the node.

p4c.set_node_custom_pie_chart(["Radiality", "Degree"], slot=3)
p4c.set_node_custom_position(node_anchor="W", x_offset=-20, slot=3)

style_name not specified, so updating "default" style.
style_name not specified, so updating "default" style.

''

p4c.notebook_export_show_image()

Enhanced Graphics

The nodes in the network are labeled with the corresponding protein names (yeast), but there is additional text information in the Node Table that could be useful to display as labels on the nodes. We are going to use the enhancedGraphics app to create a second node label for the common yeast gene name.

This involves a new step: Filling a new column with parameters for the enhancedGraphics App. This column is then mapped to a Custom Graphic slot and (optionally) positioned, like in the examples above.

Install enhancedGraphics

The enhancedGraphics app is available from the Cytoscape App Store. In Cytoscape 3.8 and above, you can install apps from R with the following function:

p4c.install_app("enhancedGraphics")

{}

{}

Define new label

The new column values have to follow a specific syntax to be recognized by the enhancedGraphics app. Here, for example, is how you set a label based on another attribute (e.g., the column called “COMMON”), specifying its size, color, outline and background:

"label: attribute=COMMON labelsize=10 color=red outline=false background=false""

For more details on the enhancedGraphics format, `see the manual <http://www.cgl.ucsf.edu/cytoscape/utilities3/enhancedcg.shtml>`__.

First, we define a dataframe with two columns: node names (“name”) and the new label (“my second label”):

import pandas as pd
all_nodes = p4c.get_all_nodes()

label_df = pd.DataFrame([all_nodes, ["label: attribute=COMMON labelsize=10 color=red outline=false background=false"] * len(all_nodes)]).transpose()

label_df.columns = ["name","my second label"]

label_df

	name	my second label
0	YDL194W	label: attribute=COMMON labelsize=10 color=red...
1	YDR277C	label: attribute=COMMON labelsize=10 color=red...
2	YBR043C	label: attribute=COMMON labelsize=10 color=red...
3	YPR145W	label: attribute=COMMON labelsize=10 color=red...
4	YER054C	label: attribute=COMMON labelsize=10 color=red...
...	...	...
325	YOR204W	label: attribute=COMMON labelsize=10 color=red...
326	YGL097W	label: attribute=COMMON labelsize=10 color=red...
327	YGR218W	label: attribute=COMMON labelsize=10 color=red...
328	YGL122C	label: attribute=COMMON labelsize=10 color=red...
329	YKR026C	label: attribute=COMMON labelsize=10 color=red...

330 rows × 2 columns

p4c.get_table_columns()

	SUID	shared name	name	selected	AverageShortestPathLength	BetweennessCentrality	ClosenessCentrality	ClusteringCoefficient	Degree	Eccentricity	...	TopologicalCoefficient	degree.layout	COMMON	gal1RGexp	gal4RGexp	gal80Rexp	gal1RGsig	gal4RGsig	gal80Rsig	isExcludedFromPaths
61	61	YDL194W	YDL194W	False	13.116935	0.0	0.076237	0.0	1	26	...	0.0	1	SNF3	0.139	0.333	0.449	0.018043	0.033961	0.011348	False
62	62	YDR277C	YDR277C	False	12.120968	0.008065	0.082502	0.0	2	25	...	0.5	2	MTH1	0.243	0.192	0.448	0.000022	0.028044	0.000573	False
63	63	YBR043C	YBR043C	False	1.5	0.0	0.666667	0.0	1	2	...	0.0	1	YBR043C	0.454	0.023	0.0	0.0	0.94178	0.999999	False
64	64	YPR145W	YPR145W	False	9.798387	0.0	0.102058	0.0	1	18	...	0.0	1	ASN1	-0.195	-0.614	-0.232	0.000032	0.0	0.001187	False
65	65	YER054C	YER054C	False	8.818548	0.044273	0.113397	0.0	2	19	...	0.583333	2	GIP2	0.057	0.206	0.247	0.16958	0.00062	0.00436	False
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
386	386	YOR204W	YOR204W	False	1.666667	0.0	0.6	0.0	1	2	...	0.0	1	DED1	-0.033	-0.056	-0.91	0.39944	0.31268	0.0	False
387	387	YGL097W	YGL097W	False	1.0	1.0	1.0	0.0	3	1	...	0.0	3	SRM1	0.16	-0.23	0.008	0.002191	0.002246	0.93826	False
388	388	YGR218W	YGR218W	False	1.666667	0.0	0.6	0.0	1	2	...	0.0	1	CRM1	-0.018	-0.001	-0.018	0.61381	0.9794	0.80969	False
389	389	YGL122C	YGL122C	False	14.375	0.024063	0.069565	0.0	3	25	...	0.333333	3	NAB2	0.174	0.02	0.187	0.000873	0.61707	0.005997	False
390	390	YKR026C	YKR026C	False	15.370968	0.0	0.065058	0.0	1	26	...	0.0	1	GCN3	-0.154	-0.501	0.292	0.000912	0.000004	0.011229	False

330 rows × 28 columns

Next, we load this dataframe into the Node Table to create and fill a new column:

p4c.load_table_data(label_df, data_key_column="name", table_key_column="name")

'Success: Data loaded in defaultnode table'

p4c.get_table_columns()

	SUID	shared name	name	selected	AverageShortestPathLength	BetweennessCentrality	ClosenessCentrality	ClusteringCoefficient	Degree	Eccentricity	...	degree.layout	COMMON	gal1RGexp	gal4RGexp	gal80Rexp	gal1RGsig	gal4RGsig	gal80Rsig	isExcludedFromPaths	my second label
61	61	YDL194W	YDL194W	False	13.116935	0.0	0.076237	0.0	1	26	...	1	SNF3	0.139	0.333	0.449	0.018043	0.033961	0.011348	False	label: attribute=COMMON labelsize=10 color=red...
62	62	YDR277C	YDR277C	False	12.120968	0.008065	0.082502	0.0	2	25	...	2	MTH1	0.243	0.192	0.448	0.000022	0.028044	0.000573	False	label: attribute=COMMON labelsize=10 color=red...
63	63	YBR043C	YBR043C	False	1.5	0.0	0.666667	0.0	1	2	...	1	YBR043C	0.454	0.023	0.0	0.0	0.94178	0.999999	False	label: attribute=COMMON labelsize=10 color=red...
64	64	YPR145W	YPR145W	False	9.798387	0.0	0.102058	0.0	1	18	...	1	ASN1	-0.195	-0.614	-0.232	0.000032	0.0	0.001187	False	label: attribute=COMMON labelsize=10 color=red...
65	65	YER054C	YER054C	False	8.818548	0.044273	0.113397	0.0	2	19	...	2	GIP2	0.057	0.206	0.247	0.16958	0.00062	0.00436	False	label: attribute=COMMON labelsize=10 color=red...
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
386	386	YOR204W	YOR204W	False	1.666667	0.0	0.6	0.0	1	2	...	1	DED1	-0.033	-0.056	-0.91	0.39944	0.31268	0.0	False	label: attribute=COMMON labelsize=10 color=red...
387	387	YGL097W	YGL097W	False	1.0	1.0	1.0	0.0	3	1	...	3	SRM1	0.16	-0.23	0.008	0.002191	0.002246	0.93826	False	label: attribute=COMMON labelsize=10 color=red...
388	388	YGR218W	YGR218W	False	1.666667	0.0	0.6	0.0	1	2	...	1	CRM1	-0.018	-0.001	-0.018	0.61381	0.9794	0.80969	False	label: attribute=COMMON labelsize=10 color=red...
389	389	YGL122C	YGL122C	False	14.375	0.024063	0.069565	0.0	3	25	...	3	NAB2	0.174	0.02	0.187	0.000873	0.61707	0.005997	False	label: attribute=COMMON labelsize=10 color=red...
390	390	YKR026C	YKR026C	False	15.370968	0.0	0.065058	0.0	1	26	...	1	GCN3	-0.154	-0.501	0.292	0.000912	0.000004	0.011229	False	label: attribute=COMMON labelsize=10 color=red...

330 rows × 29 columns

Map and position label

We now have a new column, my second label, that we can use for the mapping. This mapping does not come with a custom helper function, se we are going to use two alternative functions to prepare the passthrough mapping property and then update our visual style with the new mapping:

label_map = p4c.map_visual_property('node customgraphics 4', 'my second label', 'p')
p4c.update_style_mapping('default', label_map)

''

p4c.notebook_export_show_image()

Note: the custom graphic slot number is actulally part of the property’s name.

Finally, we position the new label in the upper right corner:

p4c.set_node_custom_position(node_anchor="E", graphic_anchor="C", x_offset=10, slot=4)

style_name not specified, so updating "default" style.

''

p4c.notebook_export_show_image()