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GSuite HyperBrowser

Statistical analysis of large-scale genomic and epigenomic track collections with hypothesis testing and Galaxy integration.

Solution by ELIXIR Norway
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Overview

GSuite HyperBrowser is a web server for statistical analysis of large-scale genomic and epigenomic data, provided by ELIXIR Norway. It is designed for life scientists and bioinformaticians who need to perform in-depth analysis of collections of genomic tracks.

The platform is built on the Galaxy framework and uses a standardized tabular format called GSuite to represent and manage track collections. It offers two user modes — a basic mode for straightforward analyses and an advanced mode for custom statistical testing — making it accessible to users with varying levels of bioinformatics expertise.

Key Features

  • Large-scale track analysis: supports complex statistical tests on collections of genomic and epigenomic tracks
  • GSuite format: organizes track collections in a simple, standardized tabular format
  • Galaxy integration: built on the Galaxy platform to support reproducible analytical workflows
  • Dual user modes: basic mode for standard analyses and advanced mode for custom statistical approaches
  • Hypothesis testing: identifies statistically significant patterns and relationships within genomic datasets

Typical Workflow

  1. Access the HyperBrowser web server
  2. Select either basic or advanced user mode based on analysis requirements
  3. Upload or import genomic tracks into the platform
  4. Use the GSuite tools to organize, process, and analyse the track collections

GSuite HyperBrowser is an open-ended service, meaning it supports a broad range of analysis scenarios. The service is hosted and maintained by ELIXIR Norway.

Meta

Domain
Genomics & Omics Analysis
Subdomain
Next-Generation Sequencing (NGS) & Sequencing Analysis
Software type(s)
Analytical Platform
Deployment type(s)
Cloud / SaaS
Industry vertical(s)
BiotechAcademic / Research
Development stage(s)
Research & Discovery
Target user(s)
Research ScientistBioinformatician / Computational Scientist
Tag(s)
Open source