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Gigascience. 2017 Jul 1;6(7):1-12. doi: 10.1093/gigascience/gix032.

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

Author information

1
Department of Informatics, University of Oslo, Oslo, Norway.
2
Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
3
Research Support Services Group, University Center for Information Technology, Oslo, Norway.
4
Statistics For Innovation, Norwegian Computing Center, Oslo, Norway.
5
Department of Mathematics, University of Oslo, Oslo, Norway.
6
Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
7
Institute for Medical Informatics, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway.
8
Department of Biosciences, University of Oslo, Oslo, Norway.
9
Norwegian Center for Stem Cell Research, Department of Immunology, Oslo University Hospital, Oslo, Norway.
10
Science Institute, University of Iceland, Reykjavik, Iceland.
11
Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Oslo, Norway.

Abstract

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.

KEYWORDS:

Galaxy; data integration; epigenomics; genome analysis; genomic track; genomics; statistical genomics

PMID:
28459977
PMCID:
PMC5493745
DOI:
10.1093/gigascience/gix032
[Indexed for MEDLINE]
Free PMC Article

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