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GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome

GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome


Titill: GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome
Höfundur: Simovski, Boris
Vodák, Daniel
Gundersen, Sveinung
Domanska, Diana
Azab, Abdulrahman
Holden, Lars
Holden, Marit
Grytten, Ivar
Rand, Knut
Drabløs, Finn
... 15 fleiri höfundar Sýna alla höfunda
Útgáfa: 2017-04-27
Tungumál: Enska
Umfang: 1-12
Háskóli/Stofnun: Háskóli Íslands
University of Iceland
Svið: Verkfræði- og náttúruvísindasvið (HÍ)
School of Engineering and Natural Sciences (UI)
Deild: Raunvísindastofnun (HÍ)
Science Institute (UI)
Birtist í: GigaScience;6(7)
ISSN: 2047-217X
DOI: 10.1093/gigascience/gix032
Efnisorð: Genomics; Epigenomics; Statistical genomics; Genome analysis; Genomic track; Galaxy; Data integration; Genamengi; Gagnasöfn; Tölfræði
URI: https://hdl.handle.net/20.500.11815/370

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Tilvitnun:

Simovski, B., Vodák, D., Gundersen, S., Domanska, D., Azab, A., Holden, L., . . . Sandve, G. K. (2017). GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome. GigaScience, 6(7), 1-12. doi:10.1093/gigascience/gix032

Útdráttur:

Background: Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. Findings: We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Conclusions: Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no.

Leyfi:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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