SOFTWARE
Hypergraph Analysis Toolbox (HAT)
HAT is a software library available for hypergraph analytics. It is available in Python and MATLAB, and we are actively working to maintain and grow the software. The main page and documentation for HAT and a short manuscript detailing its initial features are available at the following links:
Main Page: https://hypergraph-analysis-toolbox.readthedocs.io/
Manuscript: https://arxiv.org/pdf/2211.11166.pdf
To contribute, report a bug, or for additional information on HAT please contact Joshua Pickard at jpic@umich.edu
4DNvestigator
Introduction
The 4DNvestigator is a MATLAB toolbox that analyzes time-series genome-wide chromosome conformation capture (Hi-C) and gene expression (RNA-seq) data. The toolbox is available at: https://github.com/scotronq/4DNvestigator
Last updated: 10/24/2019
Installation
Install 4DNvestigator by downloading the GitHub files (see link above) and opening fdn.mlapp within MATLAB. Example scripts are also provided through GitHub, and can be run outside of the full MATLAB application.
Help / Report Bugs
For additional support or to report bugs, email Scott Ronquist at scotronq@umich.edu
4D Nucleome Analysis Toolbox
Introduction
The 4D Nucleome Analysis Toolbox (4D NAT) includes functions to load Hi-C matrices, Hi-C read data, and RNA-seq from text files, normalize Hi-C data, detect TADs, plot matrices, and explore translocations. Example scripts are available at: https://github.com/laseaman/4D_Nucleome_Analysis_Toolbox
Last updated: 5/13/2017
Installation
Install 4D NAT by downloading the GitHub files (see link above) and double clicking 4DNucleomeAanalysisToolbox.mltbx. Run examples by downloading .m files, opening them and running in MATLAB. Suggested order: Load_Normalize.m, Tad_methods.m, TranslocationAnalysis_100kb.m, TranslocationAnalysis_read.m, PhasePlane.m
Help / Report Bugs
Check to make sure the toolbox is installed by looking at: Home/Add-Ons/Manage Add-Ons and verifying that the tool box is listed there. If it is not, double click on the toolbox to install. For additional support or to report bugs, email Laura Seaman at laseaman@umich.edu
Spectral Identification of Topological Domains
Introduction
We provide a computationally efficient spectral algorithm to identify topological domains from chromosome conformation data (Hi-C data). We consider the genome as a weighted graph with vertices defined by loci on a chromosome and the edge weights given by interaction frequency between two loci. Laplacian-based graph segmentation is then applied iteratively to obtain the domains at the given compactness level.
Last updated: 5/5/2016
Installation
Install the spectral identification algorithm by downloading the ZIP folder here: Spectral Identification of Topological Domains. To verify installation, run the example script Test_Algorithm.m
Help / Report Bugs
For additional support or to report bugs, email Jie Chen at jie.chen@nwpu.edu.cn