Sybil

Sybil performs comparative genomics by clustering proteins and aligning genomic regions to identify conserved genes, gene cluster membership, and structural variation across multiple genomes.

Key Features:

• Two-Phase Protein Clustering Algorithm: A two-phase protein clustering algorithm generates clusters of proteins tailored for comparative analysis.
• Conserved Gene Detection: Identifies conserved gene sequences and their variations across genomes and maps cluster membership across genomes.
• Local Genome Alignments: Produces local alignments of genomes containing clustered genes arranged analogous to multiple sequence alignments to highlight conserved genes and cluster relationships.

Scientific Applications:

• Identification of Missed Gene Models: Detection of gene models that may have been overlooked in initial annotations.
• Single-Exon Discrepancies Analysis: Identification and analysis of discrepancies between orthologous genes, with emphasis on single-exon variations.
• Conserved Gene Synteny Exploration: Detection of large and small regions of conserved gene synteny across genomes to study structural conservation and evolutionary dynamics.
• Breakpoint Investigation: Examination of breakpoints between conserved regions to investigate genomic rearrangements.

Methodology:

Uses a two-phase protein clustering algorithm to generate protein clusters; for each protein cluster, local genome alignments are produced in a vertical stack analogous to multiple sequence alignments.