WMSA

WMSA performs weighted multiple sequence alignment of DNA, RNA, and protein sequences to identify regions of similarity for structural, functional, and evolutionary analyses.

Key Features:

• Divide-and-Conquer Strategy: Divides sequences into clusters and applies a center star strategy to align clusters, reducing computational complexity for large datasets.
• Profile-Profile Alignment: Produces progressive profile-profile alignments to merge cluster profiles into final multiple sequence alignments.
• MAFFT K-Band Integration: Leverages MAFFT algorithms, specifically K-Band, to improve alignment accuracy within profile-profile alignment steps.
• Multithread Parallelism: Employs multithreaded execution to optimize runtime and memory usage across alignment tasks.
• Optimized for Large Datasets: Balances computational resources across threads to handle extensive datasets more efficiently than single-threaded approaches.
• High-Quality Alignments: Maintains high alignment quality in highly conserved datasets and, in tests, outperformed MAFFT.
• Implementation: Implemented in C/C++ with support for Linux environments.

Scientific Applications:

• Evolutionary Biology: Identifies conserved and divergent regions to inform evolutionary relationship analyses.
• Genomics: Aligns genomic DNA sequences for comparative and structural analyses.
• Proteomics: Aligns protein sequences to detect conserved motifs and domains relevant to function.
• Phylogenetic Studies: Produces alignments suitable for downstream phylogenetic inference.
• Functional Annotation: Supports identification of functionally relevant conserved regions for annotation.
• Comparative Genomics: Enables comparison of sequence conservation and variation across genomes.

Methodology:

Sequences are clustered (divide-and-conquer), cluster profiles are created using a center star strategy, and profiles are progressively aligned via profile-profile alignment using MAFFT K-Band with multithread parallelism.