MS_Align

MS_Align compares minisatellite maps to compute optimal alignments and distance metrics under a comprehensive evolutionary model for analysis of minisatellite variation.

Key Features:

• Algorithm Design: Employs an algorithm to compare two minisatellite maps under a comprehensive evolutionary model that accounts for deletion, insertion, mutation, tandem duplication, and tandem deletion of variants.
• Optimal Alignment Computation: Computes optimal alignments between maps and assigns alignment scores as weighted sums of elementary operations, providing pairwise distance measures.
• Handling Complexity: Addresses the dependency of the optimal sequence of operations on their order of application to the map to obtain accurate comparisons.
• Variant Coding: Represents minisatellite variants using the digital coding system of Jeffreys et al. (1997).

Scientific Applications:

• Genetic Mapping and Forensic Studies: Analyzes minisatellite maps to infer genetic diversity and relationships among individuals or populations.
• Evolutionary Analysis: Reconstructs evolutionary trees from pairwise distances between minisatellite maps to investigate microevolutionary signals and population genetics.
• Population Studies (MSY1): Applied to the MSY1 (DYF155S1) locus on the Y chromosome to identify monophyletic populations within specific haplogroups.

Methodology:

Compares two minisatellite maps using an algorithm under a comprehensive evolutionary model that simulates deletion, insertion, mutation, tandem duplication, and tandem deletion; computes optimal alignments and alignment scores as weighted sums of elementary operations; and encodes variants with the Jeffreys et al. (1997) digital coding system.