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VIZBI 2013March 20-22The Broad Institute of MIT and Harvard
“How Can We Fix The Display?”Visual Analytics and HCI   Visual variables       Colour, size, motion, luminance, shape et...
Visual Design Principles   Consistency, concise, no redundancy, clarity,    focus/emphasis, truth/accuracy/detail   Can’...
Communicating Science Visually   A representation, not the thing       Photo, visualization etc.       Clarifies the wo...
Designing for Different UserGroups Software   designer’s idea of requirements  is different from user’s Make requirement...
Epigenetics   Single genotype -> multiple phenotypes   Malignant tumour analysis with IGV/cBio Portal       Network gra...
IGV/cBio Network Viewer
Caleydo / enRoute enRoute  – extract pathway data from  KEGG / WikiPathways Display pathway vertically Display experime...
Caleydo / enRoute
Visualizing RNA http://www.slideshare.net/ppgardne/vizbi  2013-visualising-rna Rfam database     Sister to Pfam (protei...
Sunburst
Visualizing Transcript Data   Non-coding RNA       Experimental/computational variation       Bowtie – parameters -> di...
Beyond the Hairball   Network graphs don’t scale up - become “hairballs”   Improvements       Clustering eg Cytoscape +...
BioTapestry
BioFabric
Structures & Features   Protein structures       Crystallography       NMR   “Sequence-Structure Gap”       Cost per ...
Aquaria WS
Comparison and Assemblies   UCSF Chimera   Molecular structure visualization       Density maps, sequence alignment, do...
Evolution of Protein Structureand Function   Protein superfamiles       Separated by billions of years       No sequenc...
Biological Networks   Network Biology       Emerging field       Elements of systems biology, bioinformatics etc.     ...
Biological Networks: Opportunities   Pathway automatic layout   Hairball – cluster to provide structure and colour   Cl...
NIH LINCS Project http://www.lincsproject.org Cellularresponse to perturbation Catalogue changes in gene expression  an...
Physiology and Function   3D Slicer       Build up 3D model from 2D images       Load files on the fly so whole model n...
Others   Developmental Anatomy       GoFigure – time-lapse        microscopyhttps://wiki.med.harvard.edu/SysBio/Megaso  ...
Posters BioTapestry  – nodes are lines Shiny – Rstudio to web application Chimera – stucture modelling & animation Bom...
Posters VIZBI   Plus     Public engagement in Australia     Working with animators e.g. The Hungry      Microbiome – in...
Posters Connectivity  Map – transcriptomics - LINCS  genome-wide transcriptional expression data Clickme – Generate HTML...
Posters InVeo    Network models of layers and connections    Layers for genome, transcriptome, proteome,     metabolome...
BioLayout Express3D Poster
BioLayout Feedback Alternative  layout algorithms Navigation – gestures Plugin architecture – DB access, file  formats ...
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VIZBI 2013 - Overview

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Overview of presentations and posters at VIZBI 2013 - Visualizing Biological Data http://vizbi.org/2013/Program/

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Transcript of "VIZBI 2013 - Overview"

  1. 1. VIZBI 2013March 20-22The Broad Institute of MIT and Harvard
  2. 2. “How Can We Fix The Display?”Visual Analytics and HCI Visual variables  Colour, size, motion, luminance, shape etc. Change detection  Size > Colour > Orientation How much realism?  Too much requires inference Animation  New - longer knowledge of static design  Back button  Speed control – many animations too fast Sweet spot of complexity vs inference  Controls to add/remove information Training / domain knowledge important  Good visualization requires shorter training Studies – eye tracking, emotional response
  3. 3. Visual Design Principles Consistency, concise, no redundancy, clarity, focus/emphasis, truth/accuracy/detail Can’t compare network layouts side by side Optical illusions – problem for heat maps High contrast for legibility Visual weight  Don’t give different things same visual weight  Use gradient of visual weights instead of colour to show change e.g not obvious purple leads to red  Then use colour to delineate e.g. different cell populations using same weighting scheme
  4. 4. Communicating Science Visually A representation, not the thing  Photo, visualization etc.  Clarifies the work (to ourselves and others) Striking photo or model  Improve lighting, angle etc  Can make look too perfect Metaphor  e.g. pin art to illustrate rastering  Avoid factual errors Hand-drawing: a representation, a process Poster design  Panels in groups  More space  Delineate text – boxes, shadows  “Visual abstract”  See large images from far away
  5. 5. Designing for Different UserGroups Software designer’s idea of requirements is different from user’s Make requirements gathering part of research User registration – can group and store
  6. 6. Epigenetics Single genotype -> multiple phenotypes Malignant tumour analysis with IGV/cBio Portal  Network graphs from transcription factors  Red/blue edges: pos/neg regulation WASHU Epigenome Browser http://epigenomegateway.wustl.edu  Genome/metadata heatmaps Genome3D  http://genomebioinfo.musc.edu/Genome3D/  Structural, genomic, epigenetic data viewer
  7. 7. IGV/cBio Network Viewer
  8. 8. Caleydo / enRoute enRoute – extract pathway data from KEGG / WikiPathways Display pathway vertically Display experimental data horizontally in groups http://www.icg.tugraz.at/project/caleydo /projects-1/enroute
  9. 9. Caleydo / enRoute
  10. 10. Visualizing RNA http://www.slideshare.net/ppgardne/vizbi 2013-visualising-rna Rfam database  Sister to Pfam (protein)  Aim to annotate all ncRNA families  Analysis of C/D box snoRNA taxonomy  Sunbursts  Concentric pie charts  External ring contains child nodes of internal ring
  11. 11. Sunburst
  12. 12. Visualizing Transcript Data Non-coding RNA  Experimental/computational variation  Bowtie – parameters -> different results RNA-Seq  Transcriptome deep dequencing, levels, isoforms  Tuxedo suite of sequencing tools  Cufflinks/Cuffdiff2  Isoform resolution and splice variants  CummeRbund  Plots + heatmaps
  13. 13. Beyond the Hairball Network graphs don’t scale up - become “hairballs” Improvements  Clustering eg Cytoscape + clusterMaker  Collapsing nodes  Statistical analysis before visualisation  3D Alternatives  BioTapestry  Create submodels and drill down  BioFabric  Nodes are horizontal lines  Edges are vertical lines
  14. 14. BioTapestry
  15. 15. BioFabric
  16. 16. Structures & Features Protein structures  Crystallography  NMR “Sequence-Structure Gap”  Cost per genome sequence has fallen  Structure resolution difficult and expensive SRS 3D – integrate sequence, structure, gene features Aquaria WS (late 2013)  Scale to large screens  Hardware acceleration  Augmented reality navigation  Structure viewer – Java applet – to be redeveloped in WebGL  Sequence viewer – D3.js  Cross-highlighting between sequence and structure
  17. 17. Aquaria WS
  18. 18. Comparison and Assemblies UCSF Chimera Molecular structure visualization  Density maps, sequence alignment, docking Animation – create storyboard like iMovie Linear interpolation morphing between frames for smooth animation Autopack – packing algorithm Different types of transition between frames  Rock, rotate, morph etc. Interaction  3D glasses  Motion detection – hand gestures  Trackpad gestures Navigation – can clip through panes of the structure WebGL export of animation storyboard structureViz Cytoscape plugin
  19. 19. Evolution of Protein Structureand Function Protein superfamiles  Separated by billions of years  No sequence similarity  Structure conservation FunTree  Annotation of evolutionary branches ITOL  Circular graph with tree of life at centre CATH  Structure classification Genome3D  Predict structural domains from protein sequence Future  Develop library of JavaScript/HTML5 components using D3.js
  20. 20. Biological Networks Network Biology  Emerging field  Elements of systems biology, bioinformatics etc.  Nature Paper: Network biology: understanding the cells functional organization. (Barabási + Oltvai 2004) Networks an anchor for other visualizations Easy for biologist to understand Pathway – a type of network Similarity networks  E.g protein-protein, chemical-chemical, co-expression
  21. 21. Biological Networks: Opportunities Pathway automatic layout Hairball – cluster to provide structure and colour Clustering – mostly partitioning  Fuzzy, time-variant Network comparisons  Between states or species  Over time e.g. post-translational modification Connect structure information to nodes Large data  Progressive disclosure  Collapsing Stop reinventing  Integrate with existing platforms’ plugin architectures Google Summer of Code BioFabric – edges just as important as nodes
  22. 22. NIH LINCS Project http://www.lincsproject.org Cellularresponse to perturbation Catalogue changes in gene expression and cellular processes Cmap Data Explorer  Query up and down-regulated genes  Search for signatures
  23. 23. Physiology and Function 3D Slicer  Build up 3D model from 2D images  Load files on the fly so whole model not in memory  WebGL export – share with collaborators  Future – WebCL GPU computing, augmented reality interaction http://goxtk.com/  WebGL library for scientific visualization Entire presentation in WebGL! http://danielhaehn.com/p/vizbi2013/
  24. 24. Others Developmental Anatomy  GoFigure – time-lapse microscopyhttps://wiki.med.harvard.edu/SysBio/Megaso n/GoFigure Genes and Geometry  3D pheotyping http://www.mouseimaging.ca/  Average voxels to find true homologous points Supramap http://supramap.org  Integrate genetic/geospatial/temporal data e.g. spread of SARS Metagenomics  QIIME microbial community analysis http://qiime.org  Kbase – predictive systems biology
  25. 25. Posters BioTapestry – nodes are lines Shiny – Rstudio to web application Chimera – stucture modelling & animation Bombastic – clustering gene expression WASHU epigenome browser Visualizing molecules  Metalwork sculptures  WebGL application
  26. 26. Posters VIZBI Plus  Public engagement in Australia  Working with animators e.g. The Hungry Microbiome – intestinal flora animation OME/OMERO – Image data management BioVis contest  Predicting impact of mutations on proteins  http://biovis.net/contest/
  27. 27. Posters Connectivity Map – transcriptomics - LINCS genome-wide transcriptional expression data Clickme – Generate HTML from R 3D modelling of Streptomyces growth in WebGL OneZoom – fractal tree of life explorer Interactive Visualization of Biomolecular Simulations – GPU ray casting Aquaria – protein structure web app TRNDiff – multiple transcriptional regulatory networks visualized in D3.js
  28. 28. Posters InVeo  Network models of layers and connections  Layers for genome, transcriptome, proteome, metabolome CBioPortal.org – cancer genomics gateway Cell Signaling Pathways  HTML5 iPad app (ProMega) Streamgraphs  Temporal changes in gene expression in marine microbial communities
  29. 29. BioLayout Express3D Poster
  30. 30. BioLayout Feedback Alternative layout algorithms Navigation – gestures Plugin architecture – DB access, file formats etc. Pathway animation – input experimental values rather than simulation Align multiple networks 3D protein structures on nodes Pre-clustering
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