HilbertVisGUI

HilbertVisGUI visualizes long vectors of genome-position-dependent integer data using Hilbert curves to reveal spatial patterns in datasets such as ChIP-chip and ChIP-Seq scores.

Key Features:

• Hilbert curve transformation: Maps genome-position-dependent data onto a two-dimensional Hilbert curve representation to preserve spatial relationships.
• Support for long integer vectors: Handles long vectors of integer data derived from genomic positions such as ChIP-chip and ChIP-Seq scores.
• Locality preservation: Maintains proximity of adjacent genomic positions in the transformed representation to reveal clusters and distributions.
• Complementary genomic visualization: Provides an alternative representation to linear genome browsers to highlight global feature distribution across the genome.

Scientific Applications:

• Detection of feature clusters: Identification of clusters or spatial patterns indicative of functional regions such as protein binding sites or transcription factor interactions.
• Comparative distribution analysis: Comparison of different genomic datasets to discern similarities and differences in feature distributions.
• Structural organization assessment: Exploration of the structural organization of genomic elements by visualizing their spatial distributions.

Methodology:

Genome-position-dependent integer data are mapped onto a Hilbert curve, transforming one-dimensional genomic coordinates into a two-dimensional layout while preserving proximity of adjacent data points.