7. Role of 3D DNA Structure & Dynamics
Cell Division
Gene Regulation
Structural Variation
Dekker et al., Nature, 2017
8. Cell Division
Gene Regulation
Enhancers: spatial proximity to control gene expression
Clustering of chromatin near lamina: gene silencing
GWAS: many variants found in non-coding regions
Structural Variation
Dekker et al., Nature, 2017
18. 3,000,000 x
3,000,000 pixels
Printed at 300 DPI
~250 x 250 meters
~830 x 830 feet
How big is a Hi-C Interaction Matrix?
Typical resolution today:
Reads mapped into 1,000 bp bins
→ ~3,000,000 x 3,000,000 matrix
for a whole genome
Printed at 300 DPI
~250 x 250 meters
~830 x 830 feet
19. 3,000,000 x
3,000,000 pixels
Printed at 300 DPI
~250 x 250 meters
~830 x 830 feet
By Sam valadi - https://www.flickr.com/photos/132084522@N05/17178926219/in/photostream/
23. 1. View interactions at different scales
From genome to individual bins
2. Compare interactions across many conditions
Two or more conditions
3. View and compare features
Within and across maps
4. Navigating an enormous data space
With few well known landmarks
5. Do all of this in a web browser
Interaction and low latency
27. Genome Interaction Data Visualization
Scale
1. Global Interactions (whole chromosome or genome)
2. Local Interactions (immediate feature neighborhood)
3. Individual Features
Encoding
1. Heatmap
2. Node-Link Diagram (here: Arc Diagram)
3. 3D
28. Genome Interaction Data Visualization
Scale
1. Global Interactions (whole chromosome or genome)
2. Local Interactions (immediate feature neighborhood)
3. Individual Features
Encoding
1. Heatmap
2. Node-Link Diagram (here: Arc Diagram)
3. 3D Illustration of concepts and models!
30. Reviewed in Yardımcı & Noble, Genome Biology, 2017, http://aidenlab.org/juicebox/
Global Interactions
Juicebox
HEATMAP
Caveat
only qualitative interpretation of color map possible
31. Wong 2010, Nature Methods & https://en.wikipedia.org/w/index.php?curid=45522095
Mini Excursion: Color
Color is a relative medium!
32. Reviewed in Yardımcı & Noble, Genome Biology, 2017, http://aidenlab.org/juicebox/
Global Interactions
Juicebox
HEATMAP
Caveat
only qualitative interpretation of color map possible
33. DOI 10.1101/121889, http://higlass.io, Kerpedjiev, Abdennur, Lekschas …, Mirny, Park, Gehlenborg
Global Interactions
HiGlass
HEATMAP
Caveat
only qualitative interpretation of color map possible
34. Reviewed in Yardımcı & Noble, Genome Biology, 2017, http://epigenomegateway.wustl.edu/
Global Interactions
Washington University
Epigenome Browser
ARC DIAGRAM
Caveats
line crossings, limited dynamic range
zooming complex
37. http://promoter.bx.psu.edu/hi-c/, Reviewed in Yardımcı & Noble, Genome Biology, 2017
Local Interactions
3D Genome Browser
HEATSTRIP
Caveat
height of triangle grows with
distance of interaction
38. Reviewed in Yardımcı & Noble, Genome Biology, 2017, http://epigenomegateway.wustl.edu/
Local Interactions
Washington University
Epigenome Browser
ARC DIAGRAM
Caveats
zooming is problematic, no context
61. • How do specific pattern or
average pattern look?
• How variable and noisy are
detected patterns?
• Are there subgroups among
the pattern?
• How are patterns related to
other data attributes?
• What does the patterns
neighborhood look like?
62. TECHNIQUES?
• Pan & Zoom
Kerpedjiev et al.: HiGlass
• Lenses / Multifocus
Rao and Card: Table Lens
Elmquist et al.: Melange
• Abstraction / Aggregation
Dunne et al.: Motif Simplification
Elmquist et al.: ZAME
• Small Multiples
Bach et al.: Multipiles
90. HiGlass HiPiler
Investigate local
and global
interactions
Small number of
features at a time
Strong focus on
local context
Investigate features
across the whole
map
View hundreds or
thousands of
features at a time
Weak support for
context
91. HiGlass HiPiler
Investigate local
and global
interactions
Small number of
features at a time
Strong focus on
local context
Investigate features
across the whole
map
View hundreds or
thousands of
features at a time
Weak support for
context
?
92. HiGlass HiPiler
Investigate local
and global
interactions
Small number of
features at a time
Strong focus on
local context
Investigate features
across the whole
map
View hundreds or
thousands of
features at a time
Weak support for
context
Dynamic
Aggregatable
Insets
96. Acknowledgements
Peter Kerpedjiev, PhD Fritz Lekschas, MSc
HARVARD MEDICAL SCHOOL HARVARD SCHOOL OF ENGINEERING &
APPLIED SCIENCES
Funding provided by
NIH COMMON FUND (U01 CA200059)
NIH NATIONAL HUMAN GENOME RESEARCH INSTITUTE (R00 HG007583)
97. Acknowledgements
Peter Kerpedjiev
Fritz Lekschas
Nezar Abdennur
Benjamin Bach
Chuck McCallum
Kasper Dinkla
Hendrik Strobelt
Jacob M Luber
Scott B Ouellette
Alaleh Ahzir
Nikhil Kumar
Jeewon Hwang
Danielle Nguyen
Burak H Alver
Job Dekker
Hanspeter Pfister
Leonid A Mirny
Peter J Park