Cytoscape Tutorial Session 2 at UT-KBRIN Bioinformatics Summit 2014 (4/11/2014)
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Transcript of Cytoscape Tutorial Session 2 at UT-KBRIN Bioinformatics Summit 2014 (4/11/2014)
Keiichiro Ono
Bioinformatics Summit 2014 4/11/2014
Cytoscape Tutorial 2: Advanced Topics
- Effective Visualization with Cytoscape
- Use Cytoscape with external data analysis tools
- Cytoscape and The Web
Part 2: Agenda
- This section is a bit conceptual rather than practical, but it is very important to understand before creating actual data visualizations
Part 2: Agenda
Effective Visualization
Now, you know…- Basic features of Cytoscape
- How to load network / table data - Basic Analysis / Filtering - Layout - Edit Visual Styles
- Ready to create great visualizations!
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YCL032W YGL208WYER074WYBL050W YLR134WYPL149W
YDR050C YMR311CYGL134WYER102W YBR112CYKL101W YNL199C
YPL222W
YLR264W
YPL089C
YNL098C
YLL028W
YBR072W
YOR326W
YJR066W
YOR039W YNL135C YPR041WYDR174W YIL074C YKL028WYOR362C
YIL162W
YNL189W
YOR212W
YPR080W
YPR145W
YLL019C
YLR284CYPL031C YFR037CYML074C YPL240CYPR048W YBR274W YBR050C YML032C
YJR022WYBR248C YDR382W YER081WYIR009W YDR244W YOL016C
YER103W YGR058WYLR256WYAL003W YOR355WYIL061C YER111C YMR309C
YPL248CYOL127W YBR019CYLR362W YGL035CYPR167C YML123C
YBL026WYLL021W YNL091W YOR178C YIL113WYLR321C YML064C YMR117C YDL194WYNR007C
YOL058WYBR045CYER065CYNL167CYNL047C YGL097WYHR071W YDL078C YDL081CYDR354W
YER145C YGR136WYDR311W YPR119WYER112W YLR214WYCR012W
YER143W YBR043CYKL204W
YGR019WYEL041W YER133W
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YKL012W YDL113CYDR299W YDL075W YDL236W YGL229CYLR377C YNL145W
YNL236W YJL030W
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YGL013C
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YHR174W
YFL038C
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YNL050CYGR046W YAL040CYLR191W YMR138WYIL045W YHR005C YNL301C
YKL211CYLR452C YPL075WYML051W YOL123W YGR088WYHR198C YMR300C
YJR060W YMR043WYPR124WYLR081W YLR319CYKL074C YOR036WYKL001C
YDR100W
YDR395W
YDR009W
YDR309C
YPR102C
YAL030W
YHR084W
YLR345W
YBR170C
YJL089WYFL026W YBR018C YGL115W YHR179WYDL215CYGR009C YOL120C
YFL017C YDR429C
YIL052C YGL073W
YGR108WYPR035W
YJL190CYOL086C YHR055CYBL005WYKR026C
YBR155W
YOR264W YKL109W
YOR167C
YDR070CYEL015W
YIL133C
YGL166WYHR030CYGL008C
YMR146C YBR160W
YOL136C
YOL051W
YBR020W YBR190WYDR323CYLR197W YFR014CYKL161C
YML054C YKR099WYLR340WYGL106W YBR093CYCL040W
YLR044C
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YEL009CYBR135W
YOR361C YGR085C
YER056CA
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YBR109C
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YER040WYDR103W YGR074WYER052C YIL160CYOR290C YLR249W
YGL153WYOR215CYGR254W YLR432WYCR084CYOR089CYGR218W YOR303W
YGL161C YLR293CYDL030WYNL036W YHR135CYER179W YDR277CYDR184CYNL312W YML114C YFL039C YOL059WYER054C YER110CYLR109W YLR116WYNL214W YBL069W
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YNR050C
YCL030C
YJL159W
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YNL069C YNL311CYDR142C YGL044CYMR044W
Great Visualization…?
Bad Visualizations
- Unfortunately, there are lots of bad data visualizations…
- Too many colors - Too many mappings - Lack of Story
YPL201C YPL211W YML007WYPL131W YOR327CYDR171W YCL067C
YCL032W YGL208WYER074WYBL050W YLR134WYPL149W
YDR050C YMR311CYGL134WYER102W YBR112CYKL101W YNL199C
YPL222W
YLR264W
YPL089C
YNL098C
YLL028W
YBR072W
YOR326W
YJR066W
YOR039W YNL135C YPR041WYDR174W YIL074C YKL028WYOR362C
YIL162W
YNL189W
YOR212W
YPR080W
YPR145W
YLL019C
YLR284CYPL031C YFR037CYML074C YPL240CYPR048W YBR274W YBR050C YML032C
YJR022WYBR248C YDR382W YER081WYIR009W YDR244W YOL016C
YER103W YGR058WYLR256WYAL003W YOR355WYIL061C YER111C YMR309C
YPL248CYOL127W YBR019CYLR362W YGL035CYPR167C YML123C
YBL026WYLL021W YNL091W YOR178C YIL113WYLR321C YML064C YMR117C YDL194WYNR007C
YOL058WYBR045CYER065CYNL167CYNL047C YGL097WYHR071W YDL078C YDL081CYDR354W
YER145C YGR136WYDR311W YPR119WYER112W YLR214WYCR012W
YER143W YBR043CYKL204W
YGR019WYEL041W YER133W
YOL149W YBR118WYAL038W YDR167WYMR058WYER079W YMR291W
YKL012W YDL113CYDR299W YDL075W YDL236W YGL229CYLR377C YNL145W
YNL236W YJL030W
YOL156W
YGL013C
YHR171W
YBL021CYMR021C
YHR174W
YFL038C
YER090WYPR062W YAR007C YNL307C YGL237CYML024WYDR335W YLR075W
YNL050CYGR046W YAL040CYLR191W YMR138WYIL045W YHR005C YNL301C
YKL211CYLR452C YPL075WYML051W YOL123W YGR088WYHR198C YMR300C
YJR060W YMR043WYPR124WYLR081W YLR319CYKL074C YOR036WYKL001C
YDR100W
YDR395W
YDR009W
YDR309C
YPR102C
YAL030W
YHR084W
YLR345W
YBR170C
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YFL017C YDR429C
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YBR155W
YOR264W YKL109W
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YDR070CYEL015W
YIL133C
YGL166WYHR030CYGL008C
YMR146C YBR160W
YOL136C
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YLR044C
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YJL203W
YEL009CYBR135W
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YBR109C
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YGL161C YLR293CYDL030WYNL036W YHR135CYER179W YDR277CYDR184CYNL312W YML114C YFL039C YOL059WYER054C YER110CYLR109W YLR116WYNL214W YBL069W
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YIL105C YDL088CYPR010C YJR048W YIL070C YEL039CYDR412WYMR108W
YOR204W YMR255W YLR175W YHR115CYNL164C YJL013C YDL063C YNL117W
YIL143CYOR315W YDR146CYLR310CYGR014WYBR217W
YNR053C
YJL036W
YNL116W
YOR120W
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YDL013W
YDR032C
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YLR153C
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YNR050C
YCL030C
YJL159W
YHR053CYPR110C?YLR258W YBL079W
YNL069C YNL311CYDR142C YGL044CYMR044W You need to learn how to avoid this and need to make something like…
MSL5
TEM1
PRP40
MUD2
HAP4HAP2
CYC1
GCY1
HAP3
YHR198C
ECI1
YEL015W
GAL1
GAL7
GAL80
GAL3
GAL11
GAL4
GAL2
MLS1
SIP4
FBP1
GAL10
SWI5
SUC2
MIG1
ADH1PGK1
CDC19
GCR1
CBF1ENO1
ENO2
MCK1
CYC7
HAP1
CTT1
NCE103
SSL2
TFB1YNL091W
TRP4
ARG1
GCN4
SKO1
HIS3
ADE4 ILV2
TIF35
TIF5 NIP1
GNA1
PRE10
PRT1
YDR070C
GPD2
RPS17A
BAS1
HIS7
RPS24B
MSL1
HIS4
PDC5
PHO84
PHO4
YNL047C YIL105C
MET16
RPL11BRPS8B
RPL10
RPL11A
CKS1
RPL31A
PHO13
PDC1
SXM1RPL34B
RPL16B
ATC1
CAR1
FCY1
RFA2
ICL1SRP1
TPI1RPL18B
RPL25
PHO5
RPS24ARPL18A
DMC1 RAP1
RPL16A
HSP42
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
- Let’s avoid pitfalls!
What is BAD Visualization?
- Lack of story - What’s the point?
- Hard to understand - Too many or too few
visual mappings - Ugly
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
MSL5
TEM1
PRP40
MUD2
HAP4HAP2
CYC1
GCY1
HAP3
YHR198C
ECI1
YEL015W
GAL1
GAL7
GAL80
GAL3
GAL11
GAL4
GAL2
MLS1
SIP4
FBP1
GAL10
SWI5
SUC2
MIG1
ADH1PGK1
CDC19
GCR1
CBF1ENO1
ENO2
MCK1
CYC7
HAP1
CTT1
NCE103
SSL2
TFB1YNL091W
TRP4
ARG1
GCN4
SKO1
HIS3
ADE4 ILV2
TIF35
TIF5 NIP1
GNA1
PRE10
PRT1
YDR070C
GPD2
RPS17A
BAS1
HIS7
RPS24B
MSL1
HIS4
PDC5
PHO84
PHO4
YNL047C YIL105C
MET16
RPL11BRPS8B
RPL10
RPL11A
CKS1
RPL31A
PHO13
PDC1
SXM1RPL34B
RPL16B
ATC1
CAR1
FCY1
RFA2
ICL1SRP1
TPI1RPL18B
RPL25
PHO5
RPS24ARPL18A
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)
“Cool” does not always mean “Effective”
- This is what I’ve learned from my past experiences…
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
3D Network View by igraph
Carpendale et al. 96. Distortion Viewing Techniques for 3-D Data
What is the Advantage?
…And My Mistakes
Experimental 3D renderer for Cytoscape
Technology Oriented, Lack of Story!
What was the problem?
… It would be more accurate to say that visual space has 2.05 dimensions.
Lessons Learned…- Introduce additional dimension / complexity to the
visualization only when it is necessary - Animation, 3D, charts on nodes, etc.
- Use minimal set of visual channels to make the visualization understandable
- Define story (or goal) before creating actual visualization
- Understand human perception
Goal of Scientific Data Visualization
- Help scientists to understand their data sets
- Tell a STORY
- 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
- 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/
An Extreme Example (I’m not saying this is bad, but…)
http://youtu.be/WTHtYZcH6fk
Don’t be Too Cool!- Cool visualizations are sometime useless for
scientists - But still good for journal cover page…
- Balance coolness and effectiveness - Think about audience (or users if it is
interactive)
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
Human Interactome data from BioGRID visualized by Cytoscape
Large Scale Visualizations are Pointless in Many Cases
Good Large-Scale Visualizations
Ultimately, you want…
SDHA
Tyrosine metabolismFH
Arginine and proline metabolism
C00149
C00122
K00239...
SUCLG2
C15973Valine
SUCLG2C00091
DLD
DLST C16254C00042
C16255DLAT C05125C00024 PDHA1
K01643...
C00417C00158 ACO1ACLY
DLD
MDH1 C00036
C15972C15973
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
OGDHOGDH
C00074PCK1
C00068
Glycolysis / Gluconeogenesis
K00169...
K01610
But this is still useful
Costanzo et al.
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
Data Visualization Tools
http://selection.datavisualization.ch/
Effective Visualization for Non-Designers
- Excellent resource for data visualization Tamara Munzner’s Web Sitehttp://www.cs.ubc.ca/~tmm/
Resources
- Jock Mackinlay. 1986. Automating the design of graphical presentations of relational information.ACM Trans. Graph. 5, 2 (April 1986), 110-141.
Effectiveness Principle
Encode most important attributes with highest ranked channels [Mackinlay 86]
Jock Mackinlay. 1986. Automating the design of graphical presentations of relational information.ACM Trans. Graph. 5, 2 (April 1986), 110-141.
Channels are NOT Equal!
- Understand human perception - Use proper channel for proper data
Jock Mackinlay. 1986. Automating the design of graphical presentations of relational information.ACM Trans. Graph. 5, 2 (April 1986), 110-141.
In Cytoscape…1. Position: Node Position 2. Length: Edge Length 3. Area: Node Size, Edge Width 4. Color: Node/Edge/Label Color 5. Density: Node/Edge/Label
Transparency
1. Position
Power of Layout
C16255C00074 C00026 C16254 C00068 C05125
Alanine
MDH1
Valine
Fatty acid biosynthesis
C00024
C00036
Fatty acid degradation
ACLY
Glyoxylate and dicarboxylate metabolism
C00022 C00068 DLST
DLDPDHA1
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
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SUCLG2
C00091 Valine
SUCLG2C00122
ACO1
C00158
CS
Fatty acid elongation
C15972C05381
OGDH
PC
PCK1
Glycolysis / Gluconeogenesis
IDH1
IDH3A...C05379
IDH1
TITLE:Citrate cycle (TCA cycle) K00239...K00174...K01610 K01643...K00169...K17753
SDHA
Tyrosine metabolismFH
Arginine and proline metabolism
C00149
C00122
K00239...
SUCLG2
C15973Valine
SUCLG2C00091
DLD
DLST C16254C00042
C16255DLAT C05125C00024 PDHA1
K01643...
C00417C00158 ACO1ACLY
DLD
MDH1 C00036
C15972C15973
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
OGDHOGDH
C00074PCK1
C00068
Glycolysis / Gluconeogenesis
K00169...
K01610
Layouts
- Some cases, manual editing is necessary - Start from tweaked automatic layout, and
then use techniques discussed later
Group Similar Nodes
Cytoscape Function for This
- Apply layout to selected nodes only
Use Case
- Show group of nodes in same cellular location
- Same functional groups
Tweak Layout Parameters
- Layout - Settings to tweak parameters
Cytoscape Function for This
Stacking & Grouping
- Manual Layout
Cytoscape Function for This
2. Length
In Cytoscape
- Edge Length - Can be used for the similarity of
the connected nodes
- Long = less related
- Short = closely related
Scaling
3. Area
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
Edge Weight to Width
SDHA
Tyrosine metabolismFH
Arginine and proline metabolism
C00149
C00122
K00239...
SUCLG2
C15973Valine
SUCLG2C00091
DLD
DLST C16254C00042
C16255DLAT C05125C00024 PDHA1
K01643...
C00417C00158 ACO1ACLY
DLD
MDH1 C00036
C15972C15973
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
OGDHOGDH
C00074PCK1
C00068
Glycolysis / Gluconeogenesis
K00169...
K01610
C00122
SDHA
FHTyrosine metabolism
Arginine and proline metabolism
K00239...
Valine
SUCLG2
C15973
DLSTSUCLG2 C00091
DLD
C16254C00042
C05125
DLD
DLAT
PC
C00022C16255C00024PDHA1 PDHA1
C15973 C15972
C00158 C00311
IDH1
ACO1
C00417
ACO1
K00169...
C00074
PCK1
C00068
Glycolysis / GluconeogenesisK01610
Alanine
Fatty acid biosynthesis
Valine
Glyoxylate and dicarboxylate metabolism
TITLE:Citrate cycle (TCA cycle)
Fatty acid degradation
Fatty acid elongation
C05379 K17753IDH3A...
C00026Ascorbate and aldarate metabolism
D-Glutamine and D-glutamate metabolism
IDH1
AlanineK00174...
OGDH
C00068
C15972
C05381OGDH
C00149
K01643...
MDH1ACLYC00036
CS
4. Color
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
Expression Values To Node Colors
Common Pitfall: Use Too Many Colors
- Simply awful
- Hard to understand
- Doesn’t tell anything!
Colors for Categorical Data
- Again, limitation of our perception — Use up to 6~7 Colors
- Preferably, 3-4
- Less is better!
5. Density
In Cytoscape
- Node/Edge/Label Transparency - Use to emphasize important region
of the network - Density of connections
- Use edge bundling for dense network
YNL036WYDR312WYNL121C
YNL183C
YMR260C
YNL213C
YNL212W
YAL054C
YJL176C
YML012W
YJL174W
YKR082W
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YNL258CYHR115C
YOR205CYNR038W
YMR197CYKR059W
YNL189W
YDL032W
YOR207CYPL217C
YBL039C
YBR078W
YBR030W
YNL068C
YJL063C
YGL120C
YLL008W
YER111C
YIR023W
YPL204W
YDL056W
YEL009C
YOR372CYGR162W
YMR012WYJL138C
YOR117WYNL085W
YOR116C
YBR011C
YDL145C
YCR053W
YIL131C YAL023CYOR272W
YDL213C
YDR207CYOR206W
YLR182WYOR039W
YKL172W
YDL014W
YJL109C
YKR081C
YPL012W
YGL228WYOL004W YBL038WYDL035C
YGL229C
YBR247CYER006W
YNL132W
YOL139C
YLR175WYKL143W
YJR105W
YNL117W
YHR090C YBR146W
YDR283C
YBR029C
YGR059W
YKL144C
YOR261CYHR200W
YDL106C
YLR025W
YOL108C
YPR187W
YOR310CYHL029C YKL016C
YMR079W
YMR198W
YMR093W
YOR210W
YMR078C
YKL014C
YGR231C
YGR232WYLL033W
YFR004W YLL034C
YLR222C
YLR129W
YLR399C
YGR145WYBR077C
YIL035C
YOR145C
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YDR208W
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YDR385W
YLR337C
YDR448W
YLR264W
YGR090W
YMR172W YOR061W
YDL116WYGL019W
YMR229C
YML069W
YDL060W
YOL116W
YDR449C
YKR060W
YKR095W
YKR057W
YPL131W
YDL075W
YPL249C-A
YPL086C
YIL133C
YER130CYKL057C
YOL040CYLL043W
YER082C
YGR253C
YBL007C
YLR409CYCR057C
YBR190WYDR447CYML026CYOR095C
YDL133WYGR214W
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YDR470CYKL156W YJL136C
YJL190CYOR235W
YIL069CYLR387C
YPL199CYGL147C YOR293W
YFL034W
YOR292CYLR441CYOR312C
YDR471W
YMR194WYML024W YOL121C
YJL177W
YGL124CYER074WYGR034W
YBL093CYFL034C-A
YLR183C
YLR184WYDL061C
YBR118WYKL006C-A
YDR064W
YLR326W
YBR189WYPR132WYLR447C
YHR142WYBR085WYDL083C
YLR325C
YNR037C
YMR128W
YNL306W
YNR035C
YGL195W
YDL029W
YDR363W-A YDR280W
YIL032C
YJR116W
YML013C-A
YHR116W
YKL020C
YDR194C YPL037CYDR422C YPR178W
YNL322C
YPL228W
YDR296W
YHL027W
YEL037CYHR078W
YKL196C
YAL053W
YDR339C
YCR003W
YOR309C
YGR186WYBR101C YIR010W
YOL036W
YCL001W-A
YCR001WYOR322C
YER117WYGL136C
YLR208W
YBL087C
YER116C
YNL178WYPL184CYHR204W
YPL143WYER101C
YGL031CYLR030W
YGL189CYDL184C
YEL008WYER131WYGL030WYDL133C-A
YOR182CYPR042C
YGR118W
YML073CYOL120C
YBR116CYOR183W
YLL045C
YPL034W YMR164CYLR439W
YAL022CYGR250C
YBL080CYHR161C YPL242C
YLL011WYNL313C
YLR056WYDR130C
YKR029CYOR056CYLR400W
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Other Tips
Avoid Data Overload
- Mapping too many attributes makes your visualization awful!
- It is hard to see the overall trend if too many channels are used in a image
X
Move Label Position
# of Visual Properties is Limited
- Use them effectively - Don’t use too much
in the same view
PRNPHNRNPUL1EDF1
USP11
STMN1
HSP90AB1
SMARCD3
SMARCA4
CCDC88A
SMARCD3TUBB
EP300
CHD8
HTT
OPTN
CLU
MIF4GD
PPARG
PSMD1
MAP4K4
ATP6V1C1
MARCH6
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!
“Great Artists Steal…”
Summary
- Learn basic principles of data visualization
- Write a story before creating visualization - What do you want to tell by the diagram?
External Tools
External Tools
- Biological data analysis is not simple! - There is no such thing: one-size-fits-all - Need to understand de-facto standard
tools to save your time
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
GraphXDocument
MongoDB
Relational
MySQL
IPython
3rd Party Apps
NetworkAnalyzer
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
GraphXDocument
MongoDB
Relational
MySQL
IPython
3rd Party Apps
NetworkAnalyzer
Data Analysis ToolsAnalysis VisualizationData Preparation
Data Analysis Tools- Languages / Platforms
- R + Bioconductor - Python + Pandas - MATLAB - Excel
- Graph analysis library - igraph - NetworkX
Data Visualization Tools
- Data visualization on web browsers are getting more and more important… - Cytoscape.js - sigma.js - D3.js
- Need more analysis functions - Cytoscape can perform network
analysis interactively, but does not have complete suite of network data analysis tools
- These days, cutting-edge methods and algorithms are implemented in Python
- Easy to implement, yet fast (because of NumPy/SciPy)
- Batch analysis - Visualize in web browsers
Why Multiple Tools?
- Avoid reinventing the wheel - igraph and NetworkX have a lots of
network analysis functions. Why should we repeat it again?
- Collaboration rather than competition - General policy for our project
Why Multiple Tools?
Glue for Applications
- There are two ways to use external tools with Cytoscape
- Common file formats - RESTful API for programatic
access (Ongoing)
- Use popular, standard, widely-used data formats !
- GraphML (Recommended) - CSV/TSV
- Not a format, but easy to process in scripting languages and spreadsheet
File-Base Data Exchange
Realistic Example
- Prepare data in Python - Load data from Bioconductor - Calculate network statistics with
igraph - Export networks and tables in
GraphML format
- Visualize it in Cytoscape
Realistic Example
- Prepare data in Python - Load data from Bioconductor - Calculate network statistics with
igraph - Export networks and tables in
GraphML format
- Visualize it in Cytoscape
Coming Soon…
- Programatic access to Cytoscape objects and functions via REST - /networks/ID/nodes/NODEID - /apply/layout?network=ID
- We need your opinion!
Communication Bus
NDEx (DB)
Browser
Cytoscape Desktop
Web and Cytoscape
- Prepare/integrate/analyze data with R/Python or traditional desktop applications
- Visualize & publish it as web apps
Trends in Data Visualization
Web!
Into The Web…
- Cytoscape is a Java desktop application - Need glue modules to use existing
Cytoscape features from web browsers
New in Cytoscape 3.1.0: Export Networks and Visual Styles to Cytoscape.js Format
JS
Integration to Cytoscape
Cytoscape.js is NOT
- Complete web application - Compatible with Cytoscape Apps - Replacement for Cytoscape
Export to Cytoscape.js Demo
Open Q&A Session
2014 Keiichiro Ono [email protected]