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Explores Hi-C and other contact map data. Juicebox allows users to zoom in and out of Hi-C maps interactively. It integrates many technologies developed for the Integrative Genomics Viewer with a broad ensemble of methods specifically designed for handling 2D contact data. Individual maps can be normalized (corrected for experimental bias), compared to one-dimensional tracks (such as gene tracks or chromatin immunoprecipitation sequencing data), and compared to 2D feature lists (such as loop and domain annotations).


Displays and compares large matrices within a web page. HiGlass is a tool for exploring large genomic data sets. It strives to create a seamless interface for zooming and exploration of massive 2D genomic data sets. Matrices are typically visualized as heatmaps. In the case of large matrices, the heatmaps are too large to render all at once. Instead, their values are aggregate and display summaries at lower resolution while allowing one to zoom in and explore them in greater detail.

QuIN / Query tool for Interaction Networks

A web-based application for visualizing, annotating, and querying chromatin interactions derived from technologies such as ChIA-PET or HiC. QuIN enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.


Enables the exploration and visualization of large genome interaction matrices based on many small regions-of-interest (ROIs) through interactive small multiples. HiPiler is an interactive visualization interface. The software is implemented as a web application consisting of a front-end interface for the visualizations and a server-side component that provides the data. HiPiler approach is not limited to exploration of genome interaction matrices but can theoretically be extended to any graph-based dataset that can be represented in a correlation matrix, which exhibits ROIs with recurrent visual patterns.


An easy-to-use open-source visualization tool to facilitate juxtaposition of Hi-C matrices with diverse genomic assay outputs, as well as to compare interaction matrices between various conditions. HiCPlotter is a command-line application written in Python with a minimum number of dependencies (namely numpy, matplotlib, and scipy) and generates coherent visual presentations of the data. It requires interaction matrix files, and is capable of displaying matrices as an interaction matrix (heatmap) and rotated half matrix (triangular plot). Additional tracks, imported from bedGraph format, can be displayed as histograms, tiles, arcs, or domains.

HIPPIE / High-throughput Identification Pipeline for Promoter Interacting Enhancer elements

A high-throughput identification pipeline for promoter interacting enhancer element to streamline the workflow from mapping raw Hi-C reads, identifying DNA-DNA interacting fragments with high confidence and quality control, detecting histone modifications and DNase hypersensitive enrichments in putative enhancer elements, to ultimately extracting possible intra- and inter-chromosomal enhancer-target gene relationships.

GeSICA / Genome Segmentation from Intra Chromosomal Associations

Allows to explore genome organization. GeSICA calculates a simple logged ratio to efficiently segment the human genome into regions with two distinct states that correspond to rich and poor functional element states. It quantifies the degree of chromatin openness by using the principle that the assumption that random short-range DNA interactions would be easier to detect in open chromatin environments, and that the calculated interaction ratio could be regarded as an index.