SLAST

SLAST performs local sequence alignment searches by identifying regions in database sequences with a high density of seed matches and applying the Smith-Waterman algorithm to compute precise local alignments.

Key Features:

• Alternative alignment strategy: Locates regions in database sequences with a high density of seed matches instead of relying on a seed-and-grow extension approach.
• Smith-Waterman algorithm utilization: Applies Smith-Waterman local alignment to the identified high-density regions to obtain optimal local alignments allowing gaps.
• Targeted computational efficiency: Concentrates computationally intensive Smith-Waterman alignments on selected regions to improve efficiency in specific use cases where exhaustive extension is unnecessary.

Scientific Applications:

• Comparative genomics: Compare sequences across species or within large genomic datasets to identify conserved regions.
• Functional annotation: Align query sequences against databases to support gene and protein annotation based on sequence similarity.
• Variant analysis: Align sequences from different individuals or populations to pinpoint mutations or genetic variants.

Methodology:

Scan database sequences to identify regions with a high concentration of seed matches to the query, then perform Smith-Waterman local alignments between the query and those regions.