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SequenceJuxtaposer: Fluid Navigation For Large-Scale Sequence Comparison in Context

SequenceJuxtaposer: Fluid Navigation For Large-Scale Sequence Comparison in Context. James Slack * , Kristian Hildebrand *† , Tamara Munzner * and Katherine St.John ¥ * University of British Columbia, † Bauhaus University Weimar, ¥ City University of New York. Overview. Introduction

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SequenceJuxtaposer: Fluid Navigation For Large-Scale Sequence Comparison in Context

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  1. SequenceJuxtaposer: Fluid Navigation For Large-ScaleSequence Comparison in Context James Slack*, Kristian Hildebrand*†, Tamara Munzner* and Katherine St.John¥ * University of British Columbia, † Bauhaus University Weimar, ¥ City University of New York

  2. Overview • Introduction • Previous Work • Interaction Metaphor • SequenceJuxtaposer • Conclusion and Future Work

  3. Introduction • Sequence visualization tool • Exploration and comparison • Accordion Drawing • Stretch and shrink rubber sheet • Borders tacked down

  4. Introduction Video

  5. Previous Work • Accordion Drawing • TreeJuxtaposer [Munzner 03] • Sequence Browsers • Ensembl [Hubbard 02], UCSC Genome Browser [Kent 02], NCBI [Wheeler 02] • MacClade [Maddison 92], VISTA [Mayor 02], phylo-VISTA [Shah 03] • Artemis [Rutherford 00], LalnView [Duret 96], BARD [Spell 03], PipMaker [Schwartz 00]

  6. Accordion Drawing • SequenceJuxtaposer guarantees 3 key properties • Context • Visibility • Frame Rate

  7. Guaranteed Context • Focus+Context • Combine overview and detail into single view • More information visible simultaneously • Avoid getting lost while exploring • Major information visualization research theme • Navigation metaphor • Rubber sheet with borders tacked down

  8. Guaranteed Visibility • Highlight marks always visible • Never fall outside of current view window • Never hidden by something in front • Never vanish, even if smaller than one pixel • Requires efficient algorithms • Explicitly checking all items too slow • Linear in number of pixels, not number of items • Details in TreeJuxtaposer paper[Munzner et al, Siggraph03]

  9. Guaranteed Frame Rate • Need realtime update • Focus+Context interaction must be fluid • 20-30 frames per second • Computer graphics challenge • Progressive rendering

  10. SequenceJuxtaposer • Fluid comparison of multiple sequences • Handles DNA and RNA sequence data • Provides searching, difference calculation

  11. SequenceJuxtaposer Video

  12. Algorithm Complexity • Sublinear: • Runtime algorithms • Linear: • User-initiated actions • Subquadratic: • Preprocessing algorithms

  13. Searching • Search for motifs • Protein/Codon search • Regular expressions supported • Results marked with guaranteed visibility

  14. Differences • Explore differences between aligned pairs • Slider controls difference threshold in realtime • Results marked with guaranteed visibility

  15. Interaction • Resizing • Expand or contract rectangular areas • Drag visible rubberband interactively

  16. Interaction • Animated transitions • Grow and shrink groups • Allow user to track visual landmarks

  17. Drawing • Very high information density • Avoid overdrawing in compressed areas • Progressive rendering • Draw for fixed time, check for user interaction • Priority queue to draw items in order of current onscreen size

  18. Drawing Video

  19. Results and Performance • Java prototype using OpenGL, GL4Java • Memory for AD data structures • significant, but linear • paper: 1.7 million base pairs • current: 20 Mbp

  20. Conclusion • Accordion Drawing for sequences • Powerful new information visualization technique • Guarantees • Context for maintaing orientation • Visibility of landmarks: searches, differences • Frame rate for realtime response to interaction • Fluid exploration of big datasets

  21. Future Work • Performance • Memory, speed • Annotation • Editing • Connecting trees and sequences • Other data types • BACs (bacterial artificial chromosomes)

  22. Open Source • Freely available from http://olduvai.sourceforge.net • SequenceJuxtaposerolduvai.sf.net/sj • TreeJuxtaposerolduvai.sf.net/tj

  23. Acknowledgements • Collaboration • David Hillis and lab members, UT-Austin • Discussions • Wayne Maddison, David Haussler, Nina Amenta • Technical writing • Ciáran Llachlan Leavitt • Funding • NSF/DEB-0121651/0121682 • German Academic Exchange Service

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