hGSuite

hGSuite organizes and analyzes large collections of high-throughput DNA sequencing datasets represented as coordinate-based genomic objects to enable metadata-informed, multi-dimensional exploratory analysis.

Key Features:

• Metadata-Informed Analysis: Leverages sample and experiment metadata such as cell types and epigenetic factors to aggregate, stratify, and interpret results.
• Data Cube Methodology: Implements a data cube framework to calculate statistics across multiple dimensions and support multi-dimensional queries and aggregations.
• Hierarchical Organization: Provides hierarchical management and layered analysis to analyze data at different levels of biological complexity.
• Coordinate-Based Data Handling: Operates on genomic objects with coordinates along a reference genome for analysis of location-specific features.
• Integration with GSuite HyperBrowser: Functions as an open-source extension to the GSuite HyperBrowser platform for large-scale genomic dataset analysis.

Scientific Applications:

• Collective analysis of sequencing datasets: Aggregates and analyzes large sets of high-throughput sequencing datasets to reveal patterns across samples and conditions.
• Comparative analysis across cell types and epigenetic states: Supports aggregation and comparison of genomic features by cell type or epigenetic modification.
• Exploratory multi-dimensional statistics: Enables calculation of statistics across metadata-defined dimensions for hypothesis generation and exploratory analysis.

Methodology:

Uses a metadata-informed data cube to organize high-throughput DNA sequencing data, calculates statistics across multiple dimensions, and applies a hierarchical structure to support layered analysis.