GC-Profile

GC-Profile segments genomic sequences using a quadratic divergence-based algorithm to identify compositionally distinct domains (isochores) and visualizes cumulative GC profiles to analyze G+C content variation.

Key Features:

• Quadratic Divergence-Based Segmentation: Uses quadratic divergence to quantify differences between nucleotide probability distributions and partition sequences into compositionally distinct domains, offering simplicity and speed compared with entropy-based methods such as Jensen-Shannon divergence.
• Cumulative GC Profile Visualization: Implements cumulative GC profile techniques to display the distribution of segmentation points and GC content trends across genomic sequences.
• Analysis of Genomic Features: Examines relationships between G+C content and genomic features including gene distributions and CpG islands to support isochore and genomic island characterization.
• Application to Human Chromosomes: Has been applied to segment human chromosome sequences to delineate isochore boundaries.

Scientific Applications:

• Isochore Structure Analysis: Characterizing isochore structures in higher eukaryotes by delineating compositionally homogeneous domains.
• Genomic Island Identification: Detecting genomic islands in prokaryotic genomes through compositional segmentation.
• Genome Organization Studies: Investigating relationships between G+C content, gene distribution, and CpG islands to inform studies of genome evolution, structure, and function.
• Large Eukaryotic Genome Segmentation: Segmenting large eukaryotic genomes, exemplified by human chromosomes, to map compositional domains.

Methodology:

Computational methods include a quadratic divergence measure for segmentation of nucleotide probability distributions and cumulative GC profile techniques for visualization, with comparison to Jensen-Shannon divergence.