- Unique identifier:
- Command line interface
- Input data:
- A different Hi-C data sets, a tree describing the hierarchical relationship between the data sets, the number of clusters k, and a mapping of regions between the different data sets
- Operating system:
- GNU General Public License version 3.0
- Software type:
- Restrictions to use:
- Output data:
- The cluster assignments of regions in each Hi-C data set
- Programming languages:
- MATLAB, Python
- Computer skills:
- Sushmita Roy <>
No open topic.
(Fotuhi Siahpirani et al., 2016)
A multi-task graph-clustering approach for chromosome conformation capture data sets identifies conserved modules of chromosomal interactions.
PMID: 27233632 DOI: 10.1186/s13059-016-0962-8
Department of Computer Sciences, University of Wisconsin, Madison, WI, USA; La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA; Wisconsin Institute for Discovery, University of Wisconsin, Madison, WI, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
This work was supported by a Computing Research Association CIFellows award (National Science Foundation (NSF) award Computing Innovation Fellowship (CIF) 1136996), by the Institute Leadership Professorship Fund from La Jolla Institute for Allergy and Immunology, in part by National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Environmental Health Sciences (NIEHS), NINDS (National Institute of Neurological Disorders and Stroke), National Institute on Deafness and Other Communication Disorders (NIDCD), and NIAAA (National Institute on Alcohol Abuse and Alcoholism) of the National Institutes of Health (NIH) under award number U54AI117924, by an NSF Career award (NSF Division of Biological Infrastructure(DBI): 1350677) and a Sloan Foundation research fellowship.
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