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1
Intro to Cytoscape
Network Visualization and
Analysis with Cytoscape
Alex Pico
apico@gladstone.ucsf.edu
Hey, early birds...
2
The Plan
• USB flash drive:
– Slides .pptx
– The “Book”
– 6 Tutorials
– Cytoscape installers (plus updated plugin)
3
The Plan
• Schedule
– Introductions (1:30)
– Overview
– Cytoscape concepts and UI
– Tutorial #1
– 10 min break
– WikiPat...
4
Introductions
• Me
– Executive Director, NRNB
– Systems Biology Group, Gladstone Institutes
– 6 Years on Cytoscape core ...
5
Why networks?
• Networks provide an integrating context for data
• Commonly understood diagrammatic
representation for c...
6
Applications of Network Biology
• Gene Function Prediction –
shows connections to sets of
genes/proteins involved in sam...
7
Applications of Networks in Disease
• Identification of disease
subnetworks – identification of
disease network subnetwo...
8
The Challenge
• Making sense out of biological networks….
9
The Challenge
• Biological networks (nodes and edges)
– Seldom tell us anything by themselves
– Analysis involves:
• Und...
10
The Challenge
11
Biological Network Taxonomy
• Pathways
– Signaling
– Metabolic
– Regulatory
– Phylogeny (could also be thought of as si...
12
Biological Network Taxonomy
• Interaction Networks
– Protein-Protein interactions
– Protein-Ligand interactions
– Genet...
13
Biological Network Taxonomy
• Similarity
– Protein-Protein similarity
– Chemical similarity
– Ligand similarity (SEA)
–...
14
Visualization of Biological Networks
• Depiction
• Data Mapping
• Layouts
• Animation
15
Depiction
• There are various ways to depict biological
networks:
– Node-Link (graph) representation
• This is what we ...
16
Data mapping
• Mapping of data values associated with graph
elements onto graph visuals
• Visual attributes
– Node fill...
17
Data mapping
• Avoid cluttering your visualization with too
much data
– Map the data you are specifically interested in...
18
Layouts
• Layouts determine the location of nodes and
(sometimes) the paths of edges
• Types:
– Simple
• Grid
• Partiti...
19
Layouts
• Types:
– Force-Directed
• simulate edges as springs
• may be weighted or unweighted
– Combining layouts
• Use...
20
Layouts
• Use layouts to convey the relationships
between the nodes
• Layout algorithms may need to be “tuned” to
fit y...
21
Animation
• Animation is useful to show changes in a
network:
– Over a time series
– Over different conditions
– Betwee...
22
Introduction to Cytoscape
• Overview
• Core Concepts
– Networks vs. Attributes
– VizMapper
– Apps
• Working with Data
–...
23
WHAT IS CYTOSCAPE?
www.cytoscape.org
 Visualization
 Integration
 Analysis
Cytoscape
24
 Open source
 Cross platform
 Consortium
University of Toronto
Cytoscape
25
Core Concepts
• Networks and Annotations
Annotations
e.g., attributes or data
Networks
e.g, biological pathways
26
Core Concepts
• Visual Mapping with VizMapper
AnnotationsNetworks
VizMapper
27
Core Concepts
• Cytoscape Apps!
http://apps.cytoscape.org
28
Cytoscape
• Common use cases
– Visualizing:
• PPI
• Pathways
– Integration:
• Expression profiles
• Other state data
– ...
29
Loading Networks
• Use import network from table:
– Excel file
– Comma or tab delimited text
30
Loading Networks
• Use import network from table:
– Excel file
– Comma or tab delimited text
• Use import network from ...
31
Loading Attributes
• Loading attributes
– Use import attribute from table
32
Loading Attributes
• Loading attributes
– Use import attribute from table
• The Data Panel
33
Tutoral #1
Introduction to Cytoscape – Part 1
http://tutorials.cytoscape.org
34
Examples/Demos
• clusterMaker
– Clustering and cluster visualizations
• Agilent LitSearch Tool
– Extracting networks fr...
37
Cytoscape 2.8 vs. Cytoscape 3
• Cytoscape 2.8:
– One network. All other networks are projections
on that network.
• Ess...
42
Loading Networks (3.0)
• Conceptually the same as 2.8
– Use import network from table:
• Excel file
• Comma or tab deli...
43
Loading Tables (3.0)
• Same as 2.8, except:
– Use Import table from file
– You need to specify the network collection
44
Data Panel
45
Visual Style Manager
46
Cytoscape 2.8 vs 3.0
• Compare and Contrast
– 3.0 is more stable
– 3.0 has improved model and UI
– 2.8 has more apps
D...
47
More Tutorals
http://tutorials.cytoscape.org
48
Tips & Tricks
• “Root graph”
– “There is one graph to rule them all….”
– The networks in Cytoscape are all “views” on a...
49
Tips & Tricks
• Network views
– When you open a large network, you will not get a
view by default
– To improve interact...
50
Tips & Tricks
• Sessions
– Sessions save pretty much everything:
• Networks
• Properties
• Visual styles
• Screen sizes...
51
Tips & Tricks
• Logging
– By default, Cytoscape writes it’s logs to the Error
Dialog: HelpError Dialog
– Can change a ...
52
Tips & Tricks
• Memory
– Cytoscape uses lots of it
– Doesn’t like to let go of it
– An occasional restart when working ...
53
Tips & Tricks
• .cytoscape directory
– Your defaults and any plugins downloaded from the
plugin manager will go here
– ...
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Network Visualization and Analysis with Cytoscape

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Introductory presentation for Network Visualization and Analysis with Cytoscape

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Network Visualization and Analysis with Cytoscape

  1. 1. 1 Intro to Cytoscape Network Visualization and Analysis with Cytoscape Alex Pico apico@gladstone.ucsf.edu Hey, early birds! USB:Cytoscape Tutorial/2.8 Installers/…
  2. 2. 2 The Plan • USB flash drive: – Slides .pptx – The “Book” – 6 Tutorials – Cytoscape installers (plus updated plugin)
  3. 3. 3 The Plan • Schedule – Introductions (1:30) – Overview – Cytoscape concepts and UI – Tutorial #1 – 10 min break – WikiPathways and Pathway Analysis (2:30) – More Tutorials… – Coffee break – Jing Wang - NetGestalt (3:30) – Q&A (4:20)
  4. 4. 4 Introductions • Me – Executive Director, NRNB – Systems Biology Group, Gladstone Institutes – 6 Years on Cytoscape core development team • GenMAPP-CS Workspaces, criteriaMapper, GO-Elite, BubbbleRouter, Mosaic, NOA, PathExplorer – Co-founder and developer of WikiPathways – Background: structural biology, pathway analysis • You?
  5. 5. 5 Why networks? • Networks provide an integrating context for data • Commonly understood diagrammatic representation for concepts and relationships • Provides structure that helps reduce underlying complexity of the data • More efficient than searching databases element-by-element • Network tools give us functionality for studying complex processes • Analysis of global characteristics of the data, e.g. degree, clustering coefficient, shortest paths, centrality, density • Identify key elements (hubs) and „interesting‟ subnets • Help elucidate mechanisms of interaction • Visualization of data superimposed upon the network • Help understand how a process is modulated or attenuated by a stimulus
  6. 6. 6 Applications of Network Biology • Gene Function Prediction – shows connections to sets of genes/proteins involved in same biological process • Detection of protein complexes/other modular structures – discover modularity & higher order organization (motifs, feedback loops) • Network evolution – biological process(s) conservation across species • Prediction of new interactions and functional associations – Statistically significant domain- domain correlations in protein interaction network to predict protein-protein or genetic interaction jActiveModules, UCSD PathBlast, UCSD mCode, University of Toronto DomainGraph, Max Planck Institute
  7. 7. 7 Applications of Networks in Disease • Identification of disease subnetworks – identification of disease network subnetworks that are transcriptionally active in disease. • Subnetwork-based diagnosis – source of biomarkers for disease classification, identify interconnected genes whose aggregate expression levels are predictive of disease state • Subnetwork-based gene association – map common pathway mechanisms affected by collection of genotypes (SNP, CNV) Agilent Literature Search Mondrian, MSKCC PinnacleZ, UCSD
  8. 8. 8 The Challenge • Making sense out of biological networks….
  9. 9. 9 The Challenge • Biological networks (nodes and edges) – Seldom tell us anything by themselves – Analysis involves: • Understanding the characteristics of the network – Modularity – Comparison with other networks (specifically random networks) – Visualization involves: • Placing nodes in a meaningful way (layouts) • Mapping biologically relevant data to the network – Node size – Node color – Edge weights
  10. 10. 10 The Challenge
  11. 11. 11 Biological Network Taxonomy • Pathways – Signaling – Metabolic – Regulatory – Phylogeny (could also be thought of as similarity)
  12. 12. 12 Biological Network Taxonomy • Interaction Networks – Protein-Protein interactions – Protein-Ligand interactions – Genetic interactions – Domain-Domain interactions – Others • Residue or atomic interactions • Cell/cell interactions • Population biology • Epidemiology • Social networks
  13. 13. 13 Biological Network Taxonomy • Similarity – Protein-Protein similarity – Chemical similarity – Ligand similarity (SEA) – Others • Tag clouds • Topic maps
  14. 14. 14 Visualization of Biological Networks • Depiction • Data Mapping • Layouts • Animation
  15. 15. 15 Depiction • There are various ways to depict biological networks: – Node-Link (graph) representation • This is what we most often think of – Partitioned Node-Link representation • Split graph into discrete partitions based on some feature – Matrix representation • Can be useful for very dense networks • Can also map information into cells of matrix – e.g. degree, color scale (heat map)
  16. 16. 16 Data mapping • Mapping of data values associated with graph elements onto graph visuals • Visual attributes – Node fill color, border color, border width, size, shape, opacity, label – Edge type, color, width, ending type, ending size, ending color • Mapping types – Passthrough (labels) – Continuous (numeric values) – Discrete (categories)
  17. 17. 17 Data mapping • Avoid cluttering your visualization with too much data – Map the data you are specifically interested in to call out meaningful differences – Mapping too much data to visual attributes may just confuse the viewer – Can always create multiple networks and map different values
  18. 18. 18 Layouts • Layouts determine the location of nodes and (sometimes) the paths of edges • Types: – Simple • Grid • Partitions – Hierarchical • layout data as a tree or hierarchy • Works best when there are no loops – Circular (Radial) • arrange nodes around a circle • could use node attributes to govern position – e.g. degree sorted
  19. 19. 19 Layouts • Types: – Force-Directed • simulate edges as springs • may be weighted or unweighted – Combining layouts • Use a general layout (force directed) for the entire graph, but use hierarchical or radial to focus on a particular portion – Multi-layer layouts • Partition graph, layout each partition then layout partitions – Many, many others
  20. 20. 20 Layouts • Use layouts to convey the relationships between the nodes • Layout algorithms may need to be “tuned” to fit your network – LayoutsSettings… menu • Lots of parameters to change layout algorithm behavior • Can also consider laying out portions of your network
  21. 21. 21 Animation • Animation is useful to show changes in a network: – Over a time series – Over different conditions – Between species
  22. 22. 22 Introduction to Cytoscape • Overview • Core Concepts – Networks vs. Attributes – VizMapper – Apps • Working with Data – Loading network from the Web – Importing networks from csv files or Excel – Importing attributes from csv files or Excel – The attribute browser • Cytoscape tips & tricks
  23. 23. 23 WHAT IS CYTOSCAPE? www.cytoscape.org  Visualization  Integration  Analysis Cytoscape
  24. 24. 24  Open source  Cross platform  Consortium University of Toronto Cytoscape
  25. 25. 25 Core Concepts • Networks and Annotations Annotations e.g., attributes or data Networks e.g, biological pathways
  26. 26. 26 Core Concepts • Visual Mapping with VizMapper AnnotationsNetworks VizMapper
  27. 27. 27 Core Concepts • Cytoscape Apps! http://apps.cytoscape.org
  28. 28. 28 Cytoscape • Common use cases – Visualizing: • PPI • Pathways – Integration: • Expression profiles • Other state data – Analysis: • Network properties • Data mapped onto network
  29. 29. 29 Loading Networks • Use import network from table: – Excel file – Comma or tab delimited text
  30. 30. 30 Loading Networks • Use import network from table: – Excel file – Comma or tab delimited text • Use import network from web services – Allows query and load from a variety of services: • Pathway commons • WikiPathways (if GPML plugin is loaded) • NCBI Entrez Eutilities • BioCyc
  31. 31. 31 Loading Attributes • Loading attributes – Use import attribute from table
  32. 32. 32 Loading Attributes • Loading attributes – Use import attribute from table • The Data Panel
  33. 33. 33 Tutoral #1 Introduction to Cytoscape – Part 1 http://tutorials.cytoscape.org
  34. 34. 34 Examples/Demos • clusterMaker – Clustering and cluster visualizations • Agilent LitSearch Tool – Extracting networks from abstracts • WikiPathways – Search and load pathway diagrams
  35. 35. 37 Cytoscape 2.8 vs. Cytoscape 3 • Cytoscape 2.8: – One network. All other networks are projections on that network. • Essentially a rooted tree • No way to duplicate nodes without sharing attributes • Cytoscape 3: – Allows multiple roots. • Can have multiple trees • Each group of networks that shares a single root is called a collection
  36. 36. 42 Loading Networks (3.0) • Conceptually the same as 2.8 – Use import network from table: • Excel file • Comma or tab delimited text • …but – Must specify if you want a new network collection (tree) – If not, you need to specify the join column
  37. 37. 43 Loading Tables (3.0) • Same as 2.8, except: – Use Import table from file – You need to specify the network collection
  38. 38. 44 Data Panel
  39. 39. 45 Visual Style Manager
  40. 40. 46 Cytoscape 2.8 vs 3.0 • Compare and Contrast – 3.0 is more stable – 3.0 has improved model and UI – 2.8 has more apps Depends on what you need and when you need it • Timing – Current release: 3.0.2 – 3.1 coming in October – 22 apps and counting!
  41. 41. 47 More Tutorals http://tutorials.cytoscape.org
  42. 42. 48 Tips & Tricks • “Root graph” – “There is one graph to rule them all….” – The networks in Cytoscape are all “views” on a single graph. – Changing the attribute for a node in one network will also change that attribute for a node with the same ID in all other loaded networks – There is no way to “copy” a node and keep the same ID – Make a copy of the session
  43. 43. 49 Tips & Tricks • Network views – When you open a large network, you will not get a view by default – To improve interactive performance, Cytoscape has the concept of “Levels of Detail” • Some visual attributes will only be apparent when you zoom in • The level of detail for various attributes can be changed in the preferences • To see what things will look like at full detail: – ViewShow Graphics Details
  44. 44. 50 Tips & Tricks • Sessions – Sessions save pretty much everything: • Networks • Properties • Visual styles • Screen sizes – Saving a session on a large screen may require some resizing when opened on your laptop
  45. 45. 51 Tips & Tricks • Logging – By default, Cytoscape writes it’s logs to the Error Dialog: HelpError Dialog – Can change a preference to write it to the console • EditPreferencesProperties… • Set logger.console to true • Don’t forget to save your preferences • Restart Cytoscape – (can also turn on debugging: cytoscape.debug, but I don’t recommend it)
  46. 46. 52 Tips & Tricks • Memory – Cytoscape uses lots of it – Doesn’t like to let go of it – An occasional restart when working with large networks is a good thing – Destroy views when you don’t need them – Java doesn’t give us a good way to get the memory right at start time • Cytoscape 2.7 does a much better job at “guessing” good default memory sizes than previous versions
  47. 47. 53 Tips & Tricks • .cytoscape directory – Your defaults and any plugins downloaded from the plugin manager will go here – Sometimes, if things get really messed up, deleting (or renaming) this directory can give you a “clean slate” • Plugin manager – “Outdated” doesn’t necessarily mean “won’t work” – Plugin authors don’t always update their plugins immediately after new releases – Click on “Show outdated plugins” to see the entire list of plugins.

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