Haplosuite

Haplosuite performs clustering and visualization of haplotypes to analyze haplotype diversity within and between populations.

Key Features:

• Novel Clustering Algorithm: Groups chromosomes by haplotypic similarity to define representative patterns within genomic regions.
• Canonical Haplotype Identification: Identifies canonical haplotypes and maps each chromosome either uniquely to a canonical haplotype or as a mosaic of multiple canonical haplotypes.
• Handling Missing Data: Accommodates incomplete data by downweighing single nucleotide polymorphisms (SNPs) with higher levels of missingness during clustering.
• Graphical Visualization (HAPVISUAL): Produces graphical representations that depict the distribution and composition of clustered haplotypes across genomic regions.
• Implementation (HAPLOSIM and HAPVISUAL): Implemented as R-based components named HAPLOSIM for clustering and HAPVISUAL for visualization.

Scientific Applications:

• Understanding Haplotype Diversity: Maps chromosomes to canonical haplotypes to characterize genetic variation and structure within or between populations.
• Reproducibility of Association Signals: Assesses whether established association signals are consistent across different populations by comparing haplotype patterns.
• Investigating Positive Selection: Analyzes haplotype diversity patterns to help identify genomic regions potentially under positive selection.

Methodology:

Input genomic haplotype data from multiple populations; apply the clustering algorithm accounting for missing SNPs to define canonical haplotypes; map chromosomes to unique or mosaic canonical haplotypes; generate graphical outputs with HAPVISUAL.