1. Keiichiro Ono
UC, San Diego
Trey Ideker Lab
Bioinformatics
Summit 2014
4/11/2014
Cytoscape
An Open Source Platform for
Biological Network Analysis and Visualization

2. -
Thanks for Attending!
- Keiichiro Ono
- Cytoscape Core Developer since 2005
- Core module design & implementation
- Area of Interest: Data Integration & Visualization
- University of California, San Diego Trey Ideker Lab

3. Made with Cytoscape

4. Agenda
- What is Cytoscape?
- Data Integration, Analysis, and
Visualization with Cytoscape
- Cytoscape Ecosystem
- Cytoscape Future Plan

5. What is Cytoscape?

6. An Open Source Platform for Biological Network Data
Integration, Analysis and Visualization
Cytoscape

7. Cytoscape
- Open Source (LGPL)
- Free for both commercial and academic use
- Developed and maintained by universities,
companies, and research institutions
- De-facto standard software in biological network
research community
- Expandable by Apps
- This is why Cytoscape is a Platform, not a
simple desktop application

9. Network Data Analysis
Analysis
Visualization

10. Network Data Analysis
Analysis
s
Visualization
Desktop
Gephi
Cytoscape
matplotlib
Cytoscape.js

11. Network Dat
Analysis
Graph Analysis
NetworkX
igraph
Cytoscape
Python
Pandas
NumPy
SciPy
Excel
IPython
3rd Party Apps
NetworkAnalyzer

12. Network Data Analysis
Analysis
Graph Analysis
NetworkX
igraph
Cytoscape
Python
Pandas
NumPy
SciPy
Excel
Visualization
Desktop
Gephi
Cytoscape
matplotlib
Web
Cytoscape.js
sigma.js
d3
NDV3
d3.chart
Google Charts
Data Storage
Graph
Neo4j
GraphX
Document
MongoDB
Relational
MySQL
IPython
3rd Party Apps
NetworkAnalyzer

13. Network?

14. Network = Nodes + Edges

15. Nodes and Edges in Biology
- Protein - Protein
- Protein - DNA
- Genetic (Epistasis)
- Synthetic lethality
- Biochemical
Reactions
- Compound - Enzyme - Compound
Cartoon representation of a complex between DNA and the protein p53
Node
Node
Edge

16. Undirected Network

17. EP300
PPARG
SMARCD3
STMN1
SMARCA4
OPTN
ATP6V1C1
PSMD1
HTT
PRNP
HNRNPUL1
CCDC88A
CLU
HSP90AB1
SMARCD3
MAP4K4
MIF4GD
USP11
MARCH6TUBB
EDF1 CHD8
Protein-Protein Interactions

18. Directed Network
KEGG Pathway (TCA Cycle) visualized by Cytoscape KGMLReader

19. Human-Curated Pathways
KEGG Pathway Visualized by Cytoscape

20. KEGG Global Map
Visualized by Cytoscape

21. The Challenge in Network Biology

22. C. Elegans Interactome from BioGRID Database
?

23. Biological Networks
- Tell us anything by themselves
- Just a big hairball…

24. Module 1
Module 2

25. In other words…

26. Module 1
Need a tool to extract
meaningful biological modules

27. Basic Use Case

28. Networks
Public Interaction Databases

29. List of
Genes

30. Other Data

33. is NOT a...
- Cytoscape is a powerful tool, but cannot do
everything
- Simulator
- Fully-featured Pathway diagram editor
- Statistical network analysis tool suite
- Still, you can implement these as Apps though

34. Our Focus

35. Large-Scale Network Analysis and Visualization
Human Interactome data from BioGRID visualized by Cytoscape

36. Agenda
- What is Cytoscape?
- Data Integration, Analysis, and
Visualization with Cytoscape
- Cytoscape Ecosystem
- Cytoscape Future Plan

37. Introduction to
Biological Network
Analysis with
Cytoscape

38. 1. Data Integration
(Load Networks and Tables)
2. Data Analysis
3. Visualization
Basic Workflow
4. Prepare for Publication

39. Network Data
Annotated
Networks
Attributes
Analyzed Data

40. Cline, et al. “Integration of biological networks and gene expression
data using Cytoscape”, Nature Protocols, 2, 2366-2382 (2007).
Protocol Paper

41. <?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns
http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
<!-- Created by igraph -->
<key id="degree" for="node" attr.name="degree" attr.type="double"/>
<key id="betweenness" for="node" attr.name="betweenness"
attr.type="double"/>
<graph id="G" edgedefault="directed">
<node id="n0">
<data key="degree">79</data>
<data key="betweenness">0</data>
</node>
<node id="n1">
<data key="degree">9</data>
<data key="betweenness">167</data>
</node>
<node id="n2">
<data key="degree">18</data>
<data key="betweenness">75</data>
</node>
<node id="n3">
<data key="degree">8</data>
<data key="betweenness">12</data>
</node>
<node id="n4">
<data key="degree">26</data>
<data key="betweenness">210</data>
</node>
<node id="n5">
<data key="degree">29</data>
<data key="betweenness">320</data>
</node>
Import Networks

42. Network Data Formats
- SIF
- GML
- XGMML
- GraphML
- BioPAX
- PSI-MI
- SBML
- KGML (KEGG)
- Excel
- Text Table
- CSV
- Tab

43. Network Data Source
- From your own experiment
- Public database
- Search known interactions by list of
genes

44. Public Interaction
Databases

45. Which Database?
- Protein - Protein
- STRING
- IntAct
- Genetic
- BioGRID
- Protein - Compound
- ChEMBL

46. Which Database?
- Human-Curated Pathways
- KEGG
- Reactome
- WikiPathways
- PathwayCommons

49. Import Tables

50. NCBI Gene ID 672
On Chromosome 17
GO Terms
DNA Repair
Cell Cycle
DNA Binding
Ensemble ID
ENSG00000012048
BRCA1

51. Data Tables for Cytoscape
- Example:
- Numeric
- Gene expression profiles
- Network statistics calculated in other
applications, such as R
- Confidence scores for edges
- Text (or categorical)
- GO annotation for genes
- List of genes related to disease X
- Targets for FDA approved drugs
- Genes on KEGG Pathway Y
- Clusters / group / community calculated
in external programs
- …

52. Your Data Sets
- Anything saved as a table can be
loaded into Cytoscape
- Excel
- Tab Delimited Document
- CSV
- As long as proper mapping key is
available, Cytoscape can map them to
your networks.

53. Mapping Key in
the Network
Mapping Key in
the Table

56. Network Data
Annotated
Networks
Attributes
Analyzed Data

57. Analysis

58. Network Analysis
- Filtering
- Calculate network statistics by
Network Analyzer
- Degree distribution,centrality, etc.
- Advanced analysis by Apps

59. Filtering (Selection)
- Simple, but powerful feature to extract sub
networks from large data sets
- Select nodes and edges with specific
conditions
- Pick nodes with degree > 5
- Select edges extracted from publication
X
- Find nodes on KEGG Pathway X

63. Other Selection Command:
First Neighbor of Nodes
CTR+6

64. Create New Sub-Network From Selection
CTR+N

65. Summary: Selection
- Create filter from your biological question:
- Select all nodes annotated with GO
term “DNA repair” and have two or
more know interaction
- Select all genes directly interact with
brca1, brca2, etc.
- Extract subnetwork by CTR+N

66. Network Data
Annotated
Networks
Attributes
Analyzed Data

67. Visualization

68. - Goal: Help others to
understand your data
- Emphasize what you
want to tell
- Use color, shape,
size of objects
effectively!
- Excellent resource for
data visualization
- Tamara Munzner’s Web Site:
http://www.cs.ubc.ca/~tmm/
Data Visualization

69. Map Attributes to Visual Properties

72. Visual Style
- Collection of mappings
from Attributes to Visual
Properties

73. Visual Style
- Example Mappings:
- Expression profiles to node color
- Object type (protein, compounds,
complex, etc.) to node shape
- Interaction type (Protein-Protein,
Protein-DNA, etc.) to edge line
style

74. Layouts

79. Previous Example

80. GCN4
HIS7
ILV2
RPL16A
CBF1
YOR264W
YGR058W
YGR136W YBR190W
YCR086W
YNL050C
ACS2
FPR1
SNP1HMO1 PRP21
TAH18
SIP4
HOM3
PGK1
RPS17A
RPL18B
HSP42
ARG1
FCY1
SRP1
MCK1
YDR412W
PHO13
PHO4
PHO84
RPS24B
PDC1
RPL18A
RPS24A
PFK27
YPT1RAP1
ENO1
SEC17
GCR1
PHO5
GDS1
TPI1
CLB2
ADH1
CDC19
ENO2
ICL1
MSN5
SNC2 SEC9
DDI1
CBF5
SNC1
SSO2
YGR203W
GCR2
HXT11
RFA2PDR3
SYF3
CAR1
PDR1
AST1
YNL047C
CLB1
TIF5
HSL1
CKS1
NIP1
YML114C
PMA1
TIF35
PRT1
RPS8B
GPD2PRE10
GNA1
TIF34
YDR070C
RLM1
HSP150
CDC6
YDL023C
YIL113W
SSN6
BFR2
KNS1
TUP1
YKL161C
SSL2
VPS21
RPL25
HIS3
TFA1
HIS4
PEP7
TFB1
NCE103
SIN4
GPA1
MSL5
ATC1
SST2
CNS1
PRP40
TOR1
BUD6
YGR046W
HSC82
MSL1
BAS1
YGL161C
SKO1
PEP12
YDR100W
YNL164C
YNL091W
SUC2
RPL42B
HSP82
MUD2
AHP1
CIN4
RPL34B
RPL11B
SXM1
RPL16B
RPL11A
RPL31A
RPL10
CUP1B
SSA4
GFD1
GCN3
HRP1
RNA15
NAB2
CHK1
APG7
YLR345W
SFH1
ADE4
RAD52
MET16
TRP4
HXT9
RFA1
HSP26
GIP1
PCL10
PHO85
PCL5
GSY2
PIG2
HSF1
GAC1
CUP1A
YOR315W
GLC7
APG12
REG2
AUT1
GIP2
APG5
GLC8
PIS1
CTT1
CYC7CLN3
SLT2
CDC42
MFA2
MCM1
MFA1
STE12
SWI4
FBP1
LYS9
DMC1
MLS1
DCP1
PCK1
GAL3
SWI5
GAL1
MIG1
GAL80
FAR1
GAL11
GAL10
HAP4
GAL4
GAL7
STE4
GAL2
GCY1
RPA135
MAM33
CYB2
YDR032C
SPC24
ASN1
HEX3
LSM8
YEL015W
PRP9
TEM1
YMR044W
ECI1
YNR053C
TAF25
MTH1
YHR198C
MPT1
GLN1
GDH2
YER116C
UGA1
SNF3YLR432W
GLN3
PDC5
YIL105C
RPS28B
RPS28A
LSM4
LSM2
HAP1
STE11
SPA2
STE50
STE5
CYC1
HAP3
YER124C
HAP2
GIC2CDC28
STE2
BAR1
ALPHA2

81. YBR190W
YCR086W
YNL050C
ACS2 SNP1 PRP21
TAH18
SIP4
PGK1
RPS17A
RPL18B
HSP42
ARG1
FCY1
SRP1
MCK1
YDR412W
PHO13
PHO4
PHO84
RPS24B
PDC1
RPL18A
RPS24A
PFK27
YPT1RAP1
ENO1
SEC17
GCR1
PHO5
GDS1
TPI1
CLB2
ADH1
CDC19
ENO2
ICL1
MSN5
SNC2 SEC9
CBF5
SNC1
SSO2
YGR203W
GCR2
YNL047C
CLB1
HSL1
ML114C
PMA1
HSP150
CDC6
YIL113W
SSL2
VPS21
RPL25
HIS3
HIS4
PEP7
TFB1
NCE103
SIN4
GPA1
MSL5
ATC1
SST
CNS1
PRP40
TOR
BUD6
HSC82
MSL1
BAS1
YGL161C
SKO1
PEP12
YDR100W
YNL164C
YNL091W
SUC2
RPL42B
HSP82
MUD2
AHP1
CIN4
PIS1
CTT
CYC7CLN3
SLT2
CDC42
MFA2
MCM1
MFA1
STE12
SWI4
FBP1
LYS9
DMC1
MLS1
DCP1
PCK1
GAL3
SWI5
GAL1
MIG1
GAL80
FAR1
GAL11
GAL10
HAP4
GAL4
GAL7
STE4
GAL2
GCY1
HEX3
LSM8
YEL015W
PRP9
TEM1
YMR044W YNR053C
TAF25
MTH1
MPT1
GDH2
YER116C
SNF3YLR432W
GLN3
PDC5
YIL105C
RPS28B
RPS28A
LSM4
LSM2
HAP1
STE11
SPA2
STE50
STE5
CYC1
HAP3
YER124C
HAP2
GIC2CDC28
STE2
BAR1
ALPHA2

82. Real World Examples
http://cytoscape-publications.tumblr.com

83. Apps

84. Cytoscape Apps
- Extension programs to
add new features to
Cytoscape (were called
Plugins)
- Large App developer/
user community
- This is why Cytoscape
is so successful in life
science community!

85. (As of 4/5/2014)
APPS.CYTOSCAPE.ORG

86. Quick Overview of Apps
A travel guide to Cytoscape plugins
!
Rintaro Saito, Michael E Smoot, Keiichiro Ono, Johannes Ruscheinski, Peng-
Liang Wang, Samad Lotia, Alexander R Pico, Gary D Bader, Trey Ideker (2012)
Nature Methods 9 (11) p. 1069-1076

87. A travel guide to
Cytoscape plugins
!
Rintaro Saito, Michael E Smoot, Keiichiro Ono, Johannes
Ruscheinski, Peng-Liang Wang, Samad Lotia, Alexander R Pico,
Gary D Bader, Trey Ideker (2012)
Nature Methods 9 (11) p. 1069-1076

88. A travel guide to Cytoscape plugins
!
Rintaro Saito, Michael E Smoot, Keiichiro Ono, Johannes Ruscheinski, Peng-Liang Wang,
Samad Lotia, Alexander R Pico, Gary D Bader, Trey Ideker (2012)
Nature Methods 9 (11) p. 1069-1076

89. Agenda
- What is Cytoscape?
- Data Integration, Analysis, and
Visualization with Cytoscape
- Cytoscape Ecosystem
- Cytoscape Future Plan

90. Cytoscape Ecosystem
JS

91. Cytoscape Family
- Version 2.x - Legacy version
- Last release for 2.x is 2.8.3.
- Version 3.x - Current production version
- Latest version: 3.1.0
- Important Note: Apps for 2.x is not
compatible with 3.x
(We have similar problem like Python…)

92. Cytoscape Family
- cytoscape.js:
Library for web
applications
JS

93. Cytoscape 3.1.0

94. JS

95. JS

96. Cytoscape.js Network Visualization Library Running on Web Browsers

97. What is cytoscape.js?
A Javascript Library for network visualization,
not a web application!
Need to write some code to use it on the web browsers…

98. Complete desktop
application for network
analysis and visualization
!
Written in Java
!
Expandable by Apps
!
For Users
A Javascript Library for
network visualization,
not a web application!
!
Written in JavaScript
!
Expandable by Extensions
!
For Developers
JS

99. Analysis
Data Integration
Cytoscape Desktop
Cytoscape.js
Visualization
Minimal Analysis
Cytoscape
Web
Desktop
Layout
Visual Style
Visual Style
Layout
Visualization

100. Integration to Cytoscape
New in Cytoscape 3.1.0:
Export Networks and Visual Styles to Cytoscape.js Format
JS

102. Export to HTML5 Session
Feature for users: you can view networks on web browsers
with Cytoscape.js
Under development… We need early adapters for testing!
JS

104. Future Plan

105. Future Plan
- Integration to external
tools
- Access from
Python, R, Perl, etc.
- More integration to
Cytoscape.js
- Cytoscape
Cyberinfrastructure
(Cytoscape CI)

106. Cytoscape CI: Background
- The size of data biologists have
to analyze is still growing
- Desktop machines are
powerful, but not enough for
large scale data analysis
- Clusters / Clouds
- Using multiple computing
resources as external service is
normal for biological data
analysis…
- Scalability
Service 1
Service 2

107. Cytoscape Cyberinfrastructure
Internet
Service 1 Service 2
NDEx (DB)
Web Browser
Cytoscape Desktop

108. App Development

109. github.com/cytoscape

110. Developer Documents
- http://opentutorials.cgl.ucsf.edu/index.php/
Portal:Cytoscape3

111. Collaboration

112. Collaboration
- Once you are ready to use Cytoscape for real-world
problems, National Resources for Network Biology
(NRNB) is always open for collaboration!
- NRNB Provides support for both of
- Scientific Research
- Application / Tool Development
- nrnb.org

113. -
- Two Google Groups
- cytoscape-
discuss@googlegroups.com
- cytoscape-
helpdesk@googlegroups.com
- ANY question is OK!
Getting Help

114. General Introduction
!
!
!
!
!
Advanced Topics
- Effective Visualization
Techniques
- External Tools
!
!
Part 2Part 1

115. Q1. How many of
you have never
used Cytoscape?

116. Q2. How many of
you regularly use
R/Python/MATLAB?

118. www.cytoscape.org

119. 2014 Keiichiro Ono
kono@ucsd.edu