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.
synchronized browsing and comparing of 1D and 2D data.
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 epigenomic data using
unsupervised deep representation learning.