gpart

gpart partitions genomes into linkage disequilibrium (LD) units and visualizes LD structure to support analysis of high-density single nucleotide polymorphism (SNP) data from next-generation sequencing (NGS).

Key Features:

• Clustering algorithms: Employs clustering algorithms to define LD blocks or analysis units composed of SNPs.
• Visualization: Produces images that display LD structure together with gene positions for up to 20,000 SNPs in a single figure.
• Computational efficiency: Optimized to process large genome sequencing datasets within time and memory constraints on standard computing environments.

Scientific Applications:

• Genetic linkage and association studies: Identifying haplotype blocks and LD units to inform association mapping of traits and diseases.
• Complex trait gene mapping: Facilitating localization of genes associated with complex traits via LD partitioning.
• Population genetics: Characterizing LD structure to study population-specific patterns of genetic variation.
• Evolutionary biology: Exploring genomic LD patterns to infer evolutionary processes affecting genetic architecture.

Methodology:

Applies clustering algorithms to SNP/genomic data to delineate regions of linkage disequilibrium and visualizes those regions alongside gene positions, with optimizations for efficient processing of large datasets.