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Juicebox.js Provides a Cloud-Based Visualization System for Hi-C Data.

James T Robinson1, Douglass Turner2, Neva C Durand3

  • 1School of Medicine, University of California San Diego, La Jolla, CA 92093, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

Cell Systems
|February 12, 2018
PubMed
Summary
This summary is machine-generated.

Juicebox.js is a cloud-based tool for exploring 3D genome (Hi-C) datasets, enabling easy visualization, sharing, and reproducible research. It simplifies creating interactive figures from raw data to publication.

Keywords:
3D genomicsHi-Ccontact domainscontact mapenhancersgenome architectureloop extrusionloopsnuclear architecturevisualization

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput chromosome conformation capture (Hi-C) experiments generate large datasets detailing three-dimensional (3D) genome organization.
  • Exploring and visualizing these complex 3D genome structures is crucial for understanding gene regulation and function.
  • Existing tools may present challenges in terms of accessibility, data sharing, and reproducibility.

Purpose of the Study:

  • To introduce Juicebox.js, a novel cloud-based web application for interactive exploration of Hi-C datasets.
  • To enhance data reproducibility and sharing in 3D genomics research.
  • To streamline the process of creating and sharing visualizations and figures from Hi-C data.

Main Methods:

  • Development of Juicebox.js as a cloud-based web application.
  • Implementation of a user-friendly interface for zooming and navigating Hi-C data, similar to Google Earth.
  • Integration of features for encoding browser state into shareable URLs.
  • Development of functionalities for creating interactive figures directly within the web application.

Main Results:

  • Juicebox.js provides an intuitive platform for exploring 3D genome contact mapping data.
  • The application facilitates data reproducibility and sharing through shareable URLs and interactive figure creation.
  • Public browsers for new Hi-C datasets can be created in under a minute without coding.
  • Integration with Juicer ensures transparency from raw reads to published figures via open-source code.

Conclusions:

  • Juicebox.js significantly improves the accessibility and usability of Hi-C data exploration.
  • The tool promotes reproducible research practices in the field of 3D genomics.
  • Juicebox.js offers a powerful and efficient solution for visualizing and sharing complex genomic interaction data.