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      HiGlass: web-based visual exploration and analysis of genome interaction maps

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          Abstract

          We present HiGlass, an open source visualization tool built on web technologies that provides a rich interface for rapid, multiplex, and multiscale navigation of 2D genomic maps alongside 1D genomic tracks, allowing users to combine various data types, synchronize multiple visualization modalities, and share fully customizable views with others. We demonstrate its utility in exploring different experimental conditions, comparing the results of analyses, and creating interactive snapshots to share with collaborators and the broader public. HiGlass is accessible online at http://higlass.io and is also available as a containerized application that can be run on any platform.

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          The online version of this article (10.1186/s13059-018-1486-1) contains supplementary material, which is available to authorized users.

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          Most cited references22

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          BigWig and BigBed: enabling browsing of large distributed datasets

          Summary: BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Availability and implementation: Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu Contact: ann@soe.ucsc.edu Supplementary information: Supplementary byte-level details of the BigWig and BigBed file formats are available at Bioinformatics online. For an in-depth description of UCSC data file formats and custom tracks, see http://genome.ucsc.edu/FAQ/FAQformat.html and http://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html
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            Cohesin is positioned in mammalian genomes by transcription, CTCF and Wapl

            Mammalian genomes are spatially organized by CCCTC-binding factor (CTCF) and cohesin into chromatin loops and topologically associated domains, which have important roles in gene regulation and recombination. By binding to specific sequences, CTCF defines contact points for cohesin-mediated long-range chromosomal cis-interactions. Cohesin is also present at these sites, but has been proposed to be loaded onto DNA elsewhere and to extrude chromatin loops until it encounters CTCF bound to DNA. How cohesin is recruited to CTCF sites, according to this or other models, is unknown. Here we show that the distribution of cohesin in the mouse genome depends on transcription, CTCF and the cohesin release factor Wings apart-like (Wapl). In CTCF-depleted fibroblasts, cohesin cannot be properly recruited to CTCF sites but instead accumulates at transcription start sites of active genes, where the cohesin-loading complex is located. In the absence of both CTCF and Wapl, cohesin accumulates in up to 70 kilobase-long regions at 3′-ends of active genes, in particular if these converge on each other. Changing gene expression modulates the position of these ‘cohesin islands’. These findings indicate that transcription can relocate mammalian cohesin over long distances on DNA, as previously reported for yeast cohesin, that this translocation contributes to positioning cohesin at CTCF sites, and that active genes can be freed from cohesin either by transcription-mediated translocation or by Wapl-mediated release.
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              Juicebox.js Provides a Cloud-Based Visualization System for Hi-C Data

              SUMMARY Contact mapping experiments such as Hi-C explore how genomes fold in 3D. Here, we introduce Juicebox.js, a cloud-based web application for exploring the resulting datasets. Like the original Juicebox application, Juicebox.js allows users to zoom in and out of such datasets using an interface similar to Google Earth. Juicebox.js also has many features designed to facilitate data reproducibility and sharing. Furthermore, Juicebox.js encodes the exact state of the browser in a shareable URL. Creating a public browser for a new Hi-C dataset does not require coding and can be accomplished in under a minute. The web app also makes it possible to create interactive figures online that can complement or replace ordinary journal figures. When combined with Juicer, this makes the entire process of data analysis transparent, insofar as every step from raw reads to published figure is publicly available as open source code.
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                Author and article information

                Contributors
                pkerp@hms.harvard.edu
                nezar@mit.edu
                lekschas@seas.harvard.edu
                Chuck_McCallum@hms.harvard.edu
                kasper.dinkla@gmail.com
                hendrik@strobelt.com
                jluber@g.harvard.edu
                Scott_Ouellette@hms.harvard.edu
                alaleh.azhir@gmail.com
                nikhilkumar516@gmail.com
                jeewonhwang@g.harvard.edu
                soohyun_lee@hms.harvard.edu
                Burak_Alver@hms.harvard.edu
                pfister@g.harvard.edu
                leonid@mit.edu
                peter_park@hms.harvard.edu
                nils@hms.harvard.edu
                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1474-7596
                1474-760X
                24 August 2018
                24 August 2018
                2018
                : 19
                : 125
                Affiliations
                [1 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Biomedical Informatics, Harvard Medical School, Countway Library, ; 10 Shattuck St, Boston, MA 02115 USA
                [2 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Computational and Systems Biology Program, MIT, ; Cambridge, USA
                [3 ]ISNI 000000041936754X, GRID grid.38142.3c, School of Engineering and Applied Sciences, , Harvard University, ; Cambridge, MA USA
                [4 ]ISNI 000000041936754X, GRID grid.38142.3c, Bioinformatics and Integrative Genomics Program, Harvard Medical School, ; Boston, MA USA
                [5 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Department of Physics, MIT, ; Cambridge, USA
                [6 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Institute for Medical Engineering and Science, MIT, ; Cambridge, USA
                Author information
                http://orcid.org/0000-0003-0327-8297
                Article
                1486
                10.1186/s13059-018-1486-1
                6109259
                30143029
                b8170f05-1f65-47a8-be9c-d24b73d15496
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 22 November 2017
                : 18 July 2018
                Funding
                Funded by: National Human Genome Research Institute (US)
                Award ID: R00 HG007583
                Award Recipient :
                Funded by: National Cancer Institute (US)
                Award ID: U01 CA200059
                Award Recipient :
                Funded by: National Human Genome Research Institute (US)
                Award ID: U54 HG007963
                Categories
                Software
                Custom metadata
                © The Author(s) 2018

                Genetics
                hi-c,data visualization,chromosome conformation,genomics
                Genetics
                hi-c, data visualization, chromosome conformation, genomics

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