Gsuite HyperBrowser version2.0b
Dataset type: Software
Data released on April 21, 2017
Simovski B; Vodak D; Gundersen S; Domanska D; Azab A; Holden L; Holden M; Grytten I; Rand K; Drablos F; Johansen M; Mora A; Lund-Andersen C; Fromm B; Eskeland R; Gabrielsen OS; Ferkingstad E; Nakken S; Bengtsen M; Nederbragt AJ; Thorarensen HS; Akse JA; Glad I; Hovig E; Sandve GK (2017): Gsuite HyperBrowser version2.0b GigaScience Database. http://dx.doi.org/10.5524/100292
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.
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 con rmatory 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.
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 Genomic HyperBrowser is a generic web-based system for finding and testing relations between high-throughput sequencing and/or other genomic datasets, making use of statistical hypothesis testing and other advanced methodology. The system can be tried out at a publicly available main web instance.
The Genomic HyperBrowser is an extension (and thus a fork) of the Galaxy framework. For more information on the Galaxy project, see the main Galaxy Github page.
Read the peer-reviewed publication(s):