Visually Exploring the Genome At Scale

Visualization Systems for 1D and 2D Epigenomic Data

The human genome is about 2 meters long and tightly folded into the cell nucleus, a sphere that is 4 million times smaller than a pinhead. How do cells avoid entangling the DNA and ensure accessibility of necessary parts? Biologists study DNA folding through the detection of pairwise physical interactions along the DNA, which results in a 3-by-3 million pixel matrix. Visualized as a heatmap, thousands of local visual patterns become apparent. Studying these patterns is like trying to understand the average layout of parks while viewing countries on a world map. Biologists need to inspect matrix patterns and correlate them to other epigenomic profiles for sensemaking of biological features. We have developed several interactive tools to explore such large epigenomic datasets at different steps. HiGlass supports synchronized browsing and comparing of 1D and 2D data. HiPiler enables local 2D pattern exploration at scale through visual decomposition. To provide guidance during navigation and exploration in 2D maps we have developed Scalable Insets. Finally, Peax is build for interactive visual pattern search in 1D data using unsupervised deep representation learning.

Introduction

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Visually Exploring How the Human Genome Folds

Tools

Publications

  1. HiGlass: web-based visual exploration and analysis of genome interaction maps

    1. Peter Kerpedjiev
    2. Nezar Abdennur
    3. Fritz Lekschas
    4. Chuck McCallum
    5. Kasper Dinkla
    6. Hendrik Strobelt
    7. Jacob M. Luber
    8. Scott B. Ouellette
    9. Alaleh Azhir
    10. Nikhil Kumar
    11. Jeewon Hwang
    12. Soohyun Lee
    13. Burak H. Alver
    14. Hanspeter Pfister
    15. Leonid A. Mirny
    16. Peter J. Park
    17. Nils Gehlenborg
    Genome Biology, 2018, 19:125. doi: 10.1186/s13059-018-1486-1
  2. HiPiler: Visual Exploration Of Large Genome Interaction Matrices With Interactive Small Multiples

    1. Fritz Lekschas
    2. Benjamin Bach
    3. Peter Kerpedjiev
    4. Nils Gehlenborg
    5. Hanspeter Pfister
    IEEE Transactions on Visualization and Computer Graphics (InfoVis), 24, 1, 522-531, 2018. doi: 10.1109/TVCG.2017.2745978
  3. Pattern-Driven Navigation in 2D Multiscale Visualizations with Scalable Insets

    1. Fritz Lekschas
    2. Michael Behrisch
    3. Benjamin Bach
    4. Peter Kerpedjiev
    5. Nils Gehlenborg
    6. Hanspeter Pfister
    bioRxiv, April 4, 2019. doi: 10.1101/301036 Preprint
  4. Peax: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning

    1. Fritz Lekschas
    2. Brant Peterson
    3. Daniel Haehn
    4. Eric Ma
    5. Nils Gehlenborg
    6. Hanspeter Pfister
    bioRxiv, April 4, 2019. doi: 10.1101/597518 Preprint