Multi-Scale Visualization Tools for Exploration of Chromosome Interaction Data

Nils Gehlenborg, PhD

http://gehlenborglab.org

HARVARD MEDICAL SCHOOL DEPARTMENT OF BIOMEDICAL INFORMATICS

@nils_gehlenborg

Acknowledgements

Peter Kerpedjiev, PhD Fritz Lekschas, MScHARVARD MEDICAL SCHOOL HARVARD SCHOOL OF ENGINEERING &

APPLIED SCIENCES

Funding provided by NIH COMMON FUND (U01 CA200059) NIH NATIONAL HUMAN GENOME RESEARCH INSTITUTE (R00 HG007583)

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 Burak H Alver Hanspeter Pfister Leonid A Mirny Peter J Park

Open Research

Demo Site: http://higlass.io

Code: https://github.com/hms-dbmi/higlass

Docker: https://hub.docker.com/r/gehlenborglab/higlass/

Preprint: http://biorxiv.org/content/early/2017/03/31/121889

HIGLASS

HIPILERDemo Site: https://flekschas.github.io/hipiler/ (beta)

Code: https://github.com/flekschas/hipiler

Preprint: http://biorxiv.org/content/early/2017/04/03/123588

DNA in the Nucleus

https://upload.wikimedia.org/wikipedia/commons/7/7a/Basketball.png

https://upload.wikimedia.org/wikipedia/commons/7/7a/Basketball.pnghttp://simplemaps.com/resources/svg-us

Chromosome Interaction Data

Rao et al., Cell, 2014

Contact Matrix

3 Million x 3 Million Cells 1 KB resolution

Visualization Techniques

Yardımcı & Noble, Genome Biology, 2017

Global Interactions

Juicebox

HEATMAP

Yardımcı & Noble, Genome Biology, 2017

Global Interactions

Juicebox

HEATMAP

Yardımcı & Noble, Genome Biology, 2017

Global Interactions

Washington University Epigenome Browser

ARC DIAGRAM

Yardımcı & Noble, Genome Biology, 2017

Local Interactions

3D Genome Browser

HEATSTRIP

Yardımcı & Noble, Genome Biology, 2017

Local Interactions

Washington University Epigenome Browser

ARC DIAGRAM

Tasks

1. View interactions at different scalesFrom genome to individual bins

2. Compare interactions across many conditions Two or more conditions

3. View and compare featuresWithin and across maps

4. Do all of this in a web browserInteraction and low latency

Technology

Cooler File

HDF5Pixi.js + D3.js + React

HiGlass Server

HiGlass Client

Django + RedisEBSChrome / Safari / Firefox EC2

https://github.com/mirnylab/cooler

Aggregation: sum adjacent cells to create lower resolution views

Tiling: partition matrices into 256x256 blocks that can be individually displayed

Dealing with Large Maps: HiGlass

1. View interactions at different scalesFrom genome to individual bins

2. Compare interactions across many conditions Two or more conditions

3. Do all of this in a web browserInteraction and low latency

Demo Time: http://higlass.io

Examples: http://higlass.io/examples/

Dealing with Many Features: HiPiler

1. View and compare featuresWithin and across maps

2. Do all of this in a web browserInteraction and low latency

Video: http://biorxiv.org/highwire/filestream/36210/field_highwire_adjunct_files/0/123588-1.mov

Take Aways

1. Good visualization comes at a cost: aggregation 2. Fast rendering is crucial: use advanced technologies 3. A flexible framework provides new opportunities

My lab is hiring postdocs!

HARVARD MEDICAL SCHOOL DEPARTMENT OF BIOMEDICAL INFORMATICS

http://gehlenborglab.org

Data visualization, analysis, and management for:

• exploration tools for data repositories • provenance graphs • genomic structural variants • dynamics of the 3D genome • cancer subtypes in patient cohorts