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Cytoscape ! Effective Visualization with Cytoscape and New Features in Cytoscape 3.1.0 ! 12/6/2013 SDCSB Workshop Keiichiro Ono Cytoscape Core Developer Team University of California, San Diego Trey Ideker Lab

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Welcome! - Keiichiro Ono - Cytoscape Core Developer since 2005 - Area of Interest: Data Integration & Visualization - University of California, San Diego Trey Ideker Lab - This presentation file will be available on my Speaker Deck account - speakerdeck.com/keiono

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Today’s Agenda - Effective Visualization with Cytoscape - Introduction to New Features of Cytoscape Version 3.1.0 - Publish your work to the web - Quick Introduction to Cytoscape.js

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- Most part of this session is lecture- style, and all slides & materials will be available on the web

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System Requirements - Mac/Windows/Linux with 64bit Java 6 or later - Cytoscape 3.1.0 Beta2 - http://chianti.ucsd.edu/cytoscape-3.1.0-beta2/ - https://github.com/keiono/cytoscape-workshop-materials - https://github.com/keiono/cytoscape-workshop- materials/blob/master/tutorialYeast.cys - https://github.com/keiono/cytoscape-workshop- materials/blob/master/tutorialGal.cys

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Effective Visualization

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I assume you already know… - Basic features of Cytoscape - How to load network / table data - Basic Analysis / Filtering - Layout - Edit Visual Styles

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YBR274W YJL159W YGL166W YGR014W YKR097W YER112W YGL097W YNL145W YIL160C YKL109W YOR327C YAL003W YLR134W YDR174W YIL070C YJR060W YHR171W YIL045W YLR319C YDR429C YDR103W YER124C YPR145W YJR022W YIL133C YER111C YBL021C YGL115W YLR197W YLL028W YLR432W YBR135W YHR135C YMR186W YDR146C YPR119W YPL031C YER145C YML007W YER102W YDL088C YIL162W YCL067C YPR080W YOR036W YGL229C YLR452C YMR309C YKL001C YNL047C YOR264W YPR167C YER103W YGL153W YLR284C YOL127W YIL061C YOR290C YLR345W YPR124W YCR084C YOR355W YFL017C YNL167C YFL038C YBL069W YNL311C YLR264W YIL015W YGL008C YEL041W YNL113W YFL026W YER052C YER062C YLR214W YML123C YNL236W YGL208W YIL069C YPL240C YGL237C YBR019C YAL040C YGR085C YDR277C YER081W YLR340W YJR048W YLR321C YJL013C YGL035C YML051W YDR395W YIR009W YDL081C YDR323C YJL030W YJR109C YNL199C YMR311C YDR184C YOR120W YLR362W YLR377C YDR244W YOL123W YHR005C YNL189W YDR309C YOR039W YJL219W YNL098C YPL222W YOR315W YDL075W YOL149W YML074C YAR007C YNL116W YLR249W YNL214W YAL038W YLR081W YGL013C YDL078C YKL211C YER054C YML054C YOR326W YDL063C YHR141C YDR335W YIL052C YOR212W YDL030W YJL089W YPR010C YMR058W YHR030C YGR218W YNL312W YGR136W YMR291W YDR142C YKR026C YOR202W YDR070C YLR256W YJL194W YGL202W YMR117C YDL013W YLR191W YBR045C YLR229C YMR043W YOL156W YBL026W YER074W YNL301C YEL009C YBR248C YMR146C YGL106W YMR044W YBL050W YDR032C YER056CA YGL122C YGL134W YMR005W YDL130W YDR354W YKL028W YBR190W YPR035W YBR170C YHR198C YBR072W YLR258W YLR109W YJL190C YHR179W YKL074C YBR160W YOL016C YNL036W YEL039C YJR066W YLL019C YER133W YDL236W YAL030W YDR299W YLR117C YPL211W YMR255W YPL131W YOR204W YDR100W YLR153C YOR310C YJL157C YBL079W YGL073W YGR203W YBR018C YCL030C YDL014W YML114C YHR115C YER065C YLR075W YHR053C YDR167W YBR155W YDR382W YNR007C YNL050C YDR311W YFR014C YGR088W YPL201C ? YEL015W YLR175W YKL161C YGR019W YNL164C YLL021W YNR050C YER090W YPR110C YML024W YLR116W YBR093C YNL091W YDL215C YOR361C YIL113W YLR310C YBR043C YBR118W YGR254W YKL101W YGR048W YMR183C YER110C YGR074W YOL120C YPR062W YGR108W YGR009C YBR109C YML064C YFL039C YOR362C YPL089C YDR461W YCL032W YBL005W YPR041W YPL149W YJL203W YCL040W YIL105C YPR113W YPL111W YGR046W YGL161C YFR037C YER179W YGR058W YOL051W YBR217W YNL154C YOR089C YNL117W YPL075W YOL086C YHR084W YER116C YER040W YMR300C YMR138W YKL012W YKR099W YDL113C YHR055C YOR303W YIL143C YPR102C YNL135C YNL069C YNR053C YDR171W YHR174W YNL216W YOR215C YOL059W YLR044C YER143W YML032C YIL074C YPR048W YOL058W YCR012W YBR020W YDR050C YHR071W YPL248C YBR112C YCR086W YOR167C YNL307C YMR021C YKL204W YDR412W YDR009W YLR293C YJL036W YDL194W YBR050C YFR034C YOR178C YMR108W YGL044C YER079W YDL023C YOL136C But it does NOT mean you can create good visualizations!

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YMR058W YKR026C YOR202W YDR070C YLR256W YJL194W YGL202W YMR043W YKL028W YLR258W YLR109W YJL190C YHR179W YKL074C YBR160W YOL016C YDL236W YPL131W YOR204W YDR100W YLR153C YOR310C YJL157C YBL079W YML114C YBR155W YDR382W YNR007C YNL050C YDR311W YFR014C YGR088W YGR019W YNL164C YLL021W YNR050C YER090W YPR110C YML024W YIL113W YGR048W YGR108W YGR009C YBR109C YML064C YFL039C YOR362C YPL089C You need to know how to turn this into…

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MUD HAP4 GC HA GAL1 GAL7 GAL80 GAL3 GAL11 GAL4 GAL2 SIP4 FBP1 GAL10 SWI5 SUC2 MIG1 ADH1 PGK1 CDC19 GCR1 CBF1 ENO1 ENO2 MCK1 NCE103 SSL2 TFB1 YNL091W TRP4 ARG1 GCN4 SKO1 HIS3 ADE4 ILV2 RPS17A BAS1 HIS7 RPS24B MSL1 HIS4 PDC5 PHO84 PHO4 YIL105C MET16 RPL11B RPS8B RPL11A RPL31A PHO13 PDC1 SXM1 RPL34B RPL16B ATC1 CAR1 FCY1 ICL1 SRP1 TPI1 RPL18B RPL25 PHO5 RPS24A RPL18A DMC1 RAP1 RPL16A HSP42

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I’m not a designer… - But learning basic principles of design and data visualization is not so hard - Creating 10/10 visualization is difficult, but 8/10 is the goal for us

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What is BAD Visualization? - Lack of story - What’s the point? - Hard to understand - Too many or too few visual mappings - Ugly

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Story (or Goal) - Example: - I want to show the changing levels of gene expression for three time points - Assign gene expression profile to the primary visual property in your visualization

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MUD HAP4 GC HA GAL1 GAL7 GAL80 GAL3 GAL11 GAL4 GAL2 SIP4 FBP1 GAL10 SWI5 SUC2 MIG1 ADH1 PGK1 CDC19 GCR1 CBF1 ENO1 ENO2 MCK1 NCE103 SSL2 TFB1 YNL091W TRP4 ARG1 GCN4 SKO1 HIS3 ADE4 ILV2 RPS17A BAS1 HIS7 RPS24B MSL1 HIS4 PDC5 PHO84 PHO4 YIL105C MET16 RPL11B RPS8B RPL11A RPL31A PHO13 PDC1 SXM1 RPL34B RPL16B ATC1 CAR1 FCY1 ICL1 SRP1 TPI1 RPL18B RPL25 PHO5 RPS24A RPL18A DMC1 RAP1 RPL16A HSP42 Map gene expression values to color Avoid using more colors in other components (edge/label) If necessary, map other data into non-overlapping visual properties (edge score to width)

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“Cool” does not always mean “Effective” - This is what I’ve learned from my past experiences…

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Case Study: 3D Visualization - Background: - In late 90’s, 3D graphics card was cheap enough for entry-level workstations - Many researchers made tons of 3D graphics applications for data visualization

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3D Network View by igraph

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Carpendale et al. 96. Distortion Viewing Techniques for 3-D Data

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What is the Advantage?

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…And My Mistakes

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Experimental 3D renderer for Cytoscape

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What was the problem? … It would be more accurate to say that visual space has 2.05 dimensions.

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Lessons Learned… - Introduce additional dimension / complexity to the visualization only when it is necessary - Animation, 3D, charts on nodes, etc. - You can do a lot of things with basic set of Visual Properties - Use minimal set of visual channels to make the visualization understandable - Define story (or goal) before creating actual visualization - Understand human perception

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Goal of Scientific Data Visualization - Help scientists to understand their data sets - Tell a STORY

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- Just follow some simple principles - Info-Graphics != Data Visualization - Art/Design : Science - Infographics 8:2 - Scientific Visualization 1:9 You Don’t Have to be a Professional Designer

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What is Good Visualization? http://www.visualcomplexity.com/vc/

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- One of the unfortunate trends in data-driven life sciences is that they increasingly use programmers to abstract data so that mundane information looks visually appealing - this is motivated by the desire to appear on the cover of the glossy life sciences journals. - Comment from Wired Magazine article “Circle of Life: The Beautiful New Way to Visualize Biological Data” http://www.wired.com/wiredscience/2013/11/wired-data-life-martin-krzywinski/

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An Extreme Example (I’m not saying this is bad, however…)

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http://youtu.be/WTHtYZcH6fk

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Visualizing Heterogeneous Data In a Diagram is HARD - Visualization itself is a research area - You should learn about commonly used techniques and principles from experts

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Don’t be Too Cool! - Cool visualizations are sometime useless for scientists - But still good for journal cover page… - Balance coolness and effectiveness

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Human Interactome data from BioGRID visualized by Cytoscape

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Large Scale Visualizations are Pointless in Many Cases

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Good Large-Scale Visualizations

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Ultimately, you want…

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SDHA Tyrosine metabolism FH Arginine and proline metabolism C00149 C00122 K00239... SUCLG2 C15973 Valine SUCLG2 C00091 DLD DLST C16254 C00042 C16255 DLAT C05125 C00024 PDHA1 K01643... C00417 C00158 ACO1 ACLY DLD MDH1 C00036 C15972 C15973 CS IDH1 C00022 ACO1 PC PDHA1 C00311 Alanine Fatty acid degradation Fatty acid biosynthesis Valine TITLE:Citrate cycle (TCA cycle) Glyoxylate and dicarboxylate metabolism Fatty acid elongation D-Glutamine and D-glutamate metabolism K17753 IDH1 Ascorbate and aldarate metabolism C00026 IDH3A... C05379 Alanine C05381 C15972 K00174... C00068 OGDH OGDH C00074 PCK1 C00068 Glycolysis / Gluconeogenesis K00169... K01610

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But this is still useful

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Costanzo et al.

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Targeting the Audience - Even meaningless (but cool) visualization is useful as a eye-catcher or journal cover page - When you need figures for your publication, minimize the noise in your visualization and keep it simple

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Effective Visualization for Non-Designers

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- Excellent resource for data visualization Tamara Munzner’s Web Site
 http://www.cs.ubc.ca/~tmm/

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Resources - Jock Mackinlay. 1986. Automating the design of graphical presentations of relational information.ACM Trans. Graph. 5, 2 (April 1986), 110-141.

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Effectiveness Principle Encode most important attributes with highest ranked channels [Mackinlay 86]

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Jock Mackinlay. 1986. Automating the design of graphical presentations of relational information.ACM Trans. Graph. 5, 2 (April 1986), 110-141.

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Channels are NOT Equal! - Understand human perception - Use proper channel for proper data

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Jock Mackinlay. 1986. Automating the design of graphical presentations of relational information.ACM Trans. Graph. 5, 2 (April 1986), 110-141.

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In Cytoscape - Position: Node Position - Length: Edge Length - Area: Node Size, Edge Width - Color: Node/Edge/Label Color - Density: Node/Edge/Label Transparency

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Position

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Power of Layout

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SDHA Tyrosine metabolism FH Arginine and proline metabolism C00149 C00122 K00239... SUCLG2 C15973 Valine SUCLG2 C00091 DLD DLST C16254 C00042 C16255 DLAT C05125 C00024 PDHA1 K01643... C00417 C00158 ACO1 ACLY DLD MDH1 C00036 C15972 C15973 CS IDH1 C00022 ACO1 PC PDHA1 C00311 Alanine Fatty acid degradation Fatty acid biosynthesis Valine TITLE:Citrate cycle (TCA cycle) Glyoxylate and dicarboxylate metabolism Fatty acid elongation D-Glutamine and D-glutamate metabolism K17753 IDH1 Ascorbate and aldarate metabolism C00026 IDH3A... C05379 Alanine C05381 C15972 K00174... C00068 OGDH OGDH C00074 PCK1 C00068 Glycolysis / Gluconeogenesis K00169... K01610

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C16255 C00074 C00026 C16254 C00068 C05125 Alanine MDH1 Valine Fatty acid biosynthesis C00024 C00036 Fatty acid degradation ACLY Glyoxylate and dicarboxylate metabolism C00022 C00068 DLST DLD PDHA1 SDHA Arginine and proline metabolism FH C00149 Tyrosine metabolism C15973 DLD DLAT C00042 D-Glutamine and D-glutamate metabolism OGDH C00417 Ascorbate and aldarate metabolism ACO1 Alanine C00311 C15972 PDHA1 C15973 SUCLG2 C00091 Valine SUCLG2 C00122 ACO1 C00158 CS Fatty acid elongation C15972 C05381 OGDH PC PCK1 Glycolysis / Gluconeogenesis IDH1 IDH3A... C05379 IDH1 TITLE:Citrate cycle (TCA cycle) K00239... K00174... K01610 K01643... K00169... K17753

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Layouts - Some cases, manual editing is necessary - Start from tweaked automatic layout, and then use techniques discussed later

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Group Similar Nodes

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Use Case - Show group of nodes in same cellular location - Same functional groups

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Tweak Layout Parameters

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Stacking & Grouping

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Exercise 1: Advanced Layout Features

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Length

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In Cytoscape - Edge Length - Can be used for the similarity of the connected nodes - Long = less related - Short = closely related

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Scaling

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Area

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In Cytoscape - Node Size / Edge Width - Two strongest visual channels for mapping your data - Use these two for your important data - Automatic layout algorithms can be applied only to selected group of nodes

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Edge Weight to Width

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SDHA Tyrosine metabolism FH Arginine and proline metabolism C00149 C00122 K00239... SUCLG2 C15973 Valine SUCLG2 C00091 DLD DLST C16254 C00042 C16255 DLAT C05125 C00024 PDHA1 K01643... C00417 C00158 ACO1 ACLY DLD MDH1 C00036 C15972 C15973 CS IDH1 C00022 ACO1 PC PDHA1 C00311 Alanine Fatty acid degradation Fatty acid biosynthesis Valine TITLE:Citrate cycle (TCA cycle) Glyoxylate and dicarboxylate metabolism Fatty acid elongation D-Glutamine and D-glutamate metabolism K17753 IDH1 Ascorbate and aldarate metabolism C00026 IDH3A... C05379 Alanine C05381 C15972 K00174... C00068 OGDH OGDH C00074 PCK1 C00068 Glycolysis / Gluconeogenesis K00169... K01610

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C00122 SDHA FH Tyrosine metabolism Arginine and proline metabolism K00239... Valine SUCLG2 C15973 DLST SUCLG2 C00091 DLD C16254 C00042 C05125 DLD DLAT PC C00022 C16255 C00024 PDHA1 PDHA1 C15973 C15972 C00158 C00311 IDH1 ACO1 C00417 ACO1 K00169... C00074 PCK1 C00068 Glycolysis / Gluconeogenesis K01610 Alanine Fatty acid biosynthesis Valine Glyoxylate and dicarboxylate metabolism TITLE:Citrate cycle (TCA cycle) Fatty acid degradation Fatty acid elongation C05379 K17753 IDH3A... C00026 Ascorbate and aldarate metabolism D-Glutamine and D-glutamate metabolism IDH1 Alanine K00174... OGDH C00068 C15972 C05381 OGDH C00149 K01643... MDH1 ACLY C00036 CS

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Color

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In Cytoscape - Node/Edge/Label Color - Less accurate, but still useful especially when you map to continuous values - Automatic layout algorithms can be applied only to selected group of nodes

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Color for  Expression Values

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Common Pitfall: Use Too Many Colors - Simply awful - Hard to understand - Doesn’t tell anything!

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Colors for Categorical Data - Again, limitation of our perception — Use up to 6~7 Colors - Preferably, 3-4 - Less is better!

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Exercise 2: Useful Coloring Features

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Density

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In Cytoscape - Node/Edge/Label Transparency - Use to emphasize important region of the network - Density of connections - Use edge bundling for dense network

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YNL036W YDR312W YNL121C YNL183C YNL213C YAL054C YJL176C YML012W YKR082W YFL048C YOR205C YNR038W YMR197C YKR059W YNL189W YDL032W YOR207C YPL217C YBL039C YBR078W YBR030W YNL068C YJL063C YGL120C YLL008W YER111C YIR023W YPL204W YDL056W YEL009C YOR372C YGR162W YMR012W YJL138C YOR117W YNL085W YOR116C YBR011C YDL145C YCR053W YIL131C YAL023C YOR272W YDL213C YDR207C YOR206W YLR182W YOR039W YKL172W YDL014W YJL109C YKR081C YPL012W YGL228W YOL004W YBL038W YDL035C YGL229C YBR247C YER006W YNL132W YOL139C YLR175W YKL143W YJR105W YNL117W YHR090C YBR146W YDR283C YBR029C YGR059W YKL144C YOR261C YHR200W YDL106C YLR025W YOL108C YPR187W YOR310C YHL029C YKL016C YMR079W YMR198W YMR093W YOR210W YMR078C YKL014C YGR231C YGR232W YLL033W YFR004W YLL034C YLR222C YLR129W YLR399C YGR145W YBR077C YIL035C YOR145C YKL015W YPL126W YDR208W YDR384C YJL191W YDR385W YLR337C YDR448W YLR264W YGR090W YMR172W YOR061W YDL116W YGL019W YMR229C YML069W YDL060W YOL116W YDR449C YKR060W YKR095W YKR057W YPL131W YDL075W YPL249C-A YPL086C YIL133C YER130C YKL057C YOL040C YLL043W YER082C YGR253C YBL007C YLR409C YCR057C YNL163C YER056C-A YEL054C L076C YOR369C W YKL006W YPL080C YMR230W 8W YHR141C YGR027C YDR470C YJL136C YOR235W YIL069C YLR387C YPL199C 147C YOR293W L034W 1C YOR312C YDR471W R194W YOL121C YJL177W YLR183C YLR184W YDL061C YBR118W -A YDR064W YLR326W 189W YPR132W YLR447C YHR142W YBR085W YDL083C YLR325C YNR037C YMR128W YNL306W YNR035C YGL195W YDL029W YDR363W-A YDR280W YIL032C YJR116W YML013C-A YHR116W YKL020C YDR194C YPL037C YDR422C YPR178W YNL322C YPL228W YDR296W YHL027W YEL037C YHR078W YKL196C YAL053W YDR339C YCR003W YOR309C YGR186W YBR101C YIR010W YOL036W YCL001W-A YCR001W YOR322C YER117W YGL136C YLR208W YBL087C YER116C YNL178W YPL184C 3W W R182C YGR118W YML073C YOL120C YBR116C YOR183W YLL045C YPL034W YMR164C YLR439W YAL022C YGR250C YBL080C YHR161C YPL242C YLL011W YNL313C YLR056W YDR130C YKR029C YOR056C YLR400W YDR405W YGR183C YGR270W YGR128C YMR296C YCR082W YNL037C YNL267W YNL116W YGL106W YDR234W YPL232W YNL059C YJR104C YNL057W YMR033W YKL112W YNL119W YGR129W YML081W YDL130W-A YDL190C YDL209C YMR005W YDL160C YHR162W YHL028W YLR055C YNL312W YOL077C YCL004W YGL122C YKL028W YGR056W YGL107C YGL222C YPL159C YKL029C YJL183W YGR268C YJL062W YJL111W YNL118C YPR018W YDL012C YEL017C-A YKL135C YDR285W YAL043C YLR293C YOR209C YDR326C YIL036W YDL105W YMR092C YCL016C YGL192W YGL092W YDR501W YNL112W YMR116C YJR042W YGL207W YDR500C YPR103W YLR367W YLR029C YOR234C YGL103W YLR333C YML064C FR031C-A YMR257C W YDR174W YDR024W YGL123W YML063W YHL001W YPR104C YGL100W YOR151C YLR061W YOR208W YMR129W YDR284C Y YNL321W YGR185C YFL018C YDR463W YIL031W YNR046W YBR211C YDL193W YPR176C YDR233C YDL208W YDL159W YDR195W YDR329C YDR245W YEL017W YLR024C YHR165C YGR252W YOL076W YOR057W YIL048W YKL190W YBR283C YGL194C YDR361C YKL060C YKL195W YBR212W YKL179C YCL001W YCL011C YLR096W YFL017W-A YKL019W YDR404C YPL036W YLR095C YAL043C-A YMR061W YPR186C YFL047W YCL017C YCL005W YDR330W YPR129W YMR060C YKL177W YHR199C YNL307C YLR229C YMR297W YML081C-A YBR284W YJL008C YCL031C YOL068C YNL149C YJR138W YIL135C YNL255C YOR147W YHR064C YKR056W YAL041W YGR119C YKL005C YOR262W YDL189W YDL122W YDL010W YDR340W YLR287C-A YGL135W YJR147W YDR450W YBL072C YJR145C YLR167W YGL104C YGR149W YPR065W YLR438C-A YJR146W YLR074C YLR403W YJL206C YNR018W YML025C YPL183W-A YNL241C YER079W YML100W YFR017C YOR028C YGL114W YEL045C YOR138C YDR259C YJL101C YMR261C YLR131C YJL067W YLR166C YOR032C YDR039C YLR075W YBR126C YKL062W YLR340W YIL149C YLR438W YEL044W YIL148W YLR105C YOR140W YEL046C W YPL090C R242C YPR131C -A YNL162W R203C YJL189W R085C YDR025W YHL016C YIL018W YOL128C YPR102C YCR093W YIL094C YDR394W YKL145W YNL262W YNL113W YOR323C YNL287W YIL076W YKR067W YGL245W YFR051C YOR150W YPR119W YDR261C YKL008C YGR234W YJL158C YNL284C YHR206W YGL137W YDR238C YJR137C YJL148W YJR110W YBR218C YDL225W YMR188C YFR040W YAL036C YKL104C YNR016C YBR025C YDL226C YER078C YOR110W YDR146C YKL007W YLR174W YJR109C YHR018C YML028W YGL062W YBR07 YMR3 YER155C YJR064W

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A KPNA3 HRAS BUB1 N FAM175A CDK8 ARIH1 CHGA ELAC2 FBXW4 FGF11 EP400 UBA1 GTF2F1 HERC2 MLH1 GTF2E1 TRIM28 HSD17B1 TAF2G PLK1 AURKA BIRC5 NEK2 YRDC PLK3 RNF2 JUN DNAJA3 CDK1 CREBBP CCNA2 ORC2L ID4 CDC25C TRRAP NEK10 XRCC3 ACACA ORC3L C11orf30 GMNN C17orf70 CASP3 PGR CHGB 9606.ENSP00000358154 RNASEL RCHY1 UIMC1 CDK13 RARB FAM175B ERBB2 PMS2 STK11 SMAD3 TP53 FANCE FANCC CHD8 RAD17 WHSC2 MED13 HIST1H4A RNF53 CREB1 PSAP MAP2K1 RPA1 WWP1 ANTXR1 PALB2 BRCC3 PEG3 FBXL7 JUND AP2B1 FLI1 TOPBP1 ECHDC1 MSH2 FANCB TSPAN9 DCUN1D1 FBXO25 MED17 CDC25A PARP2 RNF31 ELK4 TOX3 ECT2 CDK4 PPP1CA SMARCB1 SMARCC2 FBXO11 HYRC GSTP1 SMC1A MED24 PIAS4 BATF MAD2L1 PIAS1 SUMO2 CNR1 MDM2 PMS1 RNF8 SUGT1 UBA52 ELK1 MELK UBB RBM LMO7 WT1 NBR1 PPP1R3A ERCC4 RBL1 ERCC1 XRCC5 MRE11A RNF144B ETS1 WRN NMI SHFM1 EZH2 ERCC2 TUBB2A MAP3K4 HIC1 PML DCAF11 CDKN1A APLP2 CDC45 TSPAN17 NUP153 EGFR FBXL3 CTCFL SMARCE1 GATA3 CHEK2 TOP3A EIF4G1 DDB1 PAX6 KRT14 PPT1 CDK16 SMARCD2 SMARCC1 DHFR TUBA4A IGF1R RNF168 BRCA1 PPM1D JUNB MED21 FANCA HMMR CDKN1B NUSAP1 RAD9A

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Exercise 3: Opacity and Bundling

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Other Tips

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Move Label Position

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# of Visual Properties is Limited - Use them effectively - Don’t use too much in the same view

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Start from Scratch - If you are not sure you need the decoration or not, remove it - Example: Node border, edge arrow - Even labels are not always required!

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Tiling Time-Series Data - Use same network, with same layout - Copy multiple instances of the network - Tile them and apply different Visual Styles

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Avoid Data Overload - Mapping too many attributes makes your image awful! - It is hard to see the overall trend if too many channels are used in a image

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Summary - Learn basic principles of data visualization - Write a story before creating visualization - What do you want to tell by the diagram?

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Technical Trends In Data Visualization

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Web!

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Our Approach to the Web - Desktop version of Cytoscape is still important as the all-in-one platform for network visualization - However, we need to deal with requests

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Cytoscape.js Network Visualization Library Running on Web Browsers

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What is Cytoscape.js? - Cytoscape.js is: - JavaScript library for network data visualization - Running on Modern Web Browsers - Compatible with mobile devices, such as tablets and smart phones

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Cytoscape.js is NOT - Complete web application - Compatible with Cytoscape Apps - Replacement for Cytoscape

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Publish to Web - Cytoscape Desktop is your primary workspace — You can analyze network with hundreds of Apps and Cytoscape built-in features - Now you need to publish your results - As PDF (Static Image) - As Interactive Web Page (New!)

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Export to Cytoscape.js Demo

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New Features in Cytoscape 3.1

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New Features - New Style Editor - New High-Performance Filter - Commands - Export to Cytoscape.js - Updated Web Service Client (PSICQUIC)

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Citation

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App Development - Requires following skills: - Java - Maven - OSGi (for full-spec Cytoscape 3 Apps)

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App Development - For new features, we recommend to implement for 3.x series - Two ways: - Simple App (Similar to 2.x development) - Bundle App (Essentially, an OSGi bundle)

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

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github.com/cytoscape

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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

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Getting Help - Two Google Groups - [email protected] - [email protected] - ANY question is OK! - Question about slides: [email protected]

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Open Q&A Session

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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

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

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Further Readings 3 - Cytoscape Tutorial Booklet:
 
 Analysis and Visualization of Biological Networks with Cytoscape - http://www.rbvi.ucsf.edu/Outreach/Workshops/ISMBTutorial.pdf

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2013 Keiichiro Ono [email protected]