MAD-HiDTree

MAD-HiDTree distinguishes multiple accessions within a HapMap population by selecting and ranking genetic markers to enable accession validation and support downstream genome-wide association studies (GWAS).

Key Features:

• Distinguishing Score (DS): Assigns each candidate genetic marker a distinguishing score (DS) that quantifies its ability to differentiate accessions and prioritizes markers with higher percentages of homozygous genotypes.
• Set-Partitioning Algorithm: Employs a set-partitioning approach that recursively partitions sets of accessions to select optimal markers for discrimination.
• Hierarchical Decision Tree Construction: Constructs a hierarchical decision tree in which each path represents selected markers and their corresponding homozygous genotypes for accession differentiation.

Scientific Applications:

• HapMap accession validation: Validates HapMap accessions prior to GWAS to ensure specificity and integrity of genetic data.
• Application to Medicago truncatula: Applied to the Medicago truncatula HapMap population to distinguish 262 accessions.
• Experimental validation: Selected markers were validated by PCR experiments to confirm their utility in accession identification.

Methodology:

Calculating the DS for each marker, applying set-partitioning (recursive partitioning) to identify optimal markers, and building a hierarchical decision tree based on these markers.