Introduction to Biological Network Analysis and Visualization with Cytoscape Part1
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Introduction to biological network analysis and visualization with Cytoscape (using the latest version 3.4).
This is a first half of the lecture for Applied Bioinformatics lecture at TSRI.
Introduction to Biological Network Analysis and Visualization with Cytoscape Part1
Introduction to Biological Network
Analysis and Visualization with
Cytoscape
Keiichiro Ono
Cytoscape Core Developer Team
UC, San Diego Trey Ideker Lab / National Resource for Network Biology
5/10/2016 The Scripps Research Institute
Lecture 1: Basics
Keiichiro Ono
Cytoscape Core Developer
since 2005
@UCSD Trey Ideker Lab
Area of Interest:
Biological Data Integration &
Visualization
Agenda
• Lecture 1 (Today):
Introduction to Biological Network
Analysis and Visualization
• What is the benefits of biological
network analysis and visualization?
• Introduction to Cytoscape
• Preview of Lecture 2: cyREST
• Lecture 2:
Reproducible Analysis & Visualization
• Introduction to Jupyter Notebook
• Create a reproducible network
visualization workflows with Python
All documents, data, and code are available here:
https://github.com/idekerlab/tsri-lecture
Networks Pathways
Collection of binary interactions Human-curated / detailed
Large Scale Small Scale
Generated from omics-data Constructed from literature
Benefits of Network Analysis
- You have list of N genes from your
screening
- Now you want to know:
- Relationships among those
genes
- Functions
- etc.
Screening 1
PPARG
TCF7L2
RETN
IRS1
HNF1A
HNF4A
KCNJ11
GCK
LIPC
PTPN1
ABCC8
ENPP1
HNF1B
Benefits of Network Analysis
- You can see the relationships among the group
of biological entities
- Find drag targets
- Overrepresented functions AND their
connections
Gene List to Network to Biological Insight
- How?
- You need to search, integrate, and visualize
multiple data sources
This is what you will learn in this lecture
Cytoscape
- Open Source (LGPL)
- Free for both commercial and academic use
- Developed and maintained by universities,
companies, and research institutions
- UC, San Diego
- University of Toronto
- UC, San Francisco
- ISB
- And collaborators world-wide
Cytoscape
- De-facto standard software in biological network
research community
- Large User and Developer Community
- Expandable by Apps
- This is why Cytoscape is a Platform, not a
simple desktop application
Creating Visualizations in Cytoscape
Name Type
BRCA1 gene
MAP2K1 gene
C05981 compound
• Mapping from Type to Node Shape
• Mapping from Type to Node Color
C05981
BRCA1
MAP2K1
Creating mappings from data points
to Visual Properties
Cytoscape Apps
- Extension programs to
add new features to
Cytoscape
- formerly called Plugins
- Large App developer/
user community
- This is why Cytoscape
is so successful in life
science community!
Overview of App Ecosystem
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
Tools
• In some cases, you can get exact same result using different tools
• Example: Data preparation (cleansing / cleansing)
• But if you choose right tools, you can do it 100x faster than
others.
• ex: Re-formatting complex data sets
• Excel vs Python Script
• Some recommendations:
• R/Bioconductor, Python/Pandas, Git/GitHub/Gist
- 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
Design is complicated,
because humans are complicated.
Design is a process to avoid bad designs.
Mike Bostock (New York Times Visualization Team. Creator of D3.js)
It is hard to generalize the design process, but we
can avoid pitfalls by following some basic rules.
Avoid Data Overload
• Mapping too many attributes makes your visualization
awful!
• It is hard to see the overall trend of your data sets if too
many channels are used in a image
NCBI Gene ID 672
On Chromosome 17
GO Terms
DNA Repair
Cell Cycle
DNA Binding
Ensemble ID
ENSG00000012048
BRCA1
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
- …
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.
Visual Styles
- Defaults + Mappings
- Expression values to node color
- Gene function to node shape
- Interaction detection method to edge line
type
- Confidence score to edge width
Data Controls The View
• Photoshop / Illustrator
• You control the pixels and objects on the display
• Data Visualization Tools (including Cytoscape)
• Data points are mapped to visual properties
• Color
• Size
Further Readings
• My presentation slides
• http://www.slideshare.net/keiono
• This deck of will be uploaded today
Further Readings 1
- Introduction to Network Biology
- Deciphering Protein–Protein Interactions. Part I. Experimental
Techniques and Databases
Shoemaker BA, Panchenko AR (2007) Deciphering Protein–Protein
Interactions. Part I. Experimental Techniques and Databases. PLoS
Comput Biol 3(3): e42.doi:10.1371/journal.pcbi.0030042
- Deciphering Protein–Protein Interactions. Part II. Computational
Methods to Predict Protein and Domain Interaction Partners
Shoemaker BA, Panchenko AR (2007) Deciphering Protein–Protein
Interactions. Part II. Computational Methods to Predict Protein and
Domain Interaction Partners. PLoS Comput Biol 3(4): e43. doi:10.1371/
journal.pcbi.0030043
Further Readings 2
- Overview of Cytoscape Apps (Plugins)
- 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
- Sample Protocol (based on 2.x)
− Integration of biological networks and gene expression data using
Cytoscape
Cline, et al. Nature Protocols, 2, 2366-2382 (2007).
Further Readings 3
- Cytoscape Tutorial Booklet:
Analysis and Visualization of Biological Networks with Cytoscape
- http://www.rbvi.ucsf.edu/Outreach/Workshops/ISMBTutorial.pdf