Neptune

Neptune identifies differentially abundant genomic loci in bacterial populations using k-mer-based matching and probabilistic comparative-genomics methods.

Key Features:

• Exact k-mer matching with mismatch accommodation: Uses exact k-mer matching while allowing mismatches to locate genomic signatures with high precision.
• Probabilistic loci discovery: Employs probabilistic models rather than heuristic strategies to identify loci that are common in target groups and rare in non-target groups.
• Parallel computing for efficiency: Leverages parallel computing to handle large datasets and reduce processing time.
• Assembly-based locus extraction without multiple sequence alignments: Identifies and extracts relevant loci from draft genome assemblies without requiring multiple sequence alignments or other computationally intensive comparative analyses.
• Sensitivity and specificity evaluation: Demonstrates rapid identification of regions that are both sensitive and specific based on testing with simulated and real datasets.
• Differential abundance detection: Detects sequences significantly represented in target groups while absent or rare in non-target groups.

Scientific Applications:

• Comparative bacterial genomics: Discovery of loci that distinguish bacterial populations and lineages.
• Pathogenomics: Identification of pathogen-associated genomic signatures relevant to virulence and epidemiology.
• Trait-associated locus discovery: Detection of loci associated with specific traits such as antibiotic resistance or virulence factors.
• Study of bacterial evolution: Analysis of differentially abundant genomic content to infer evolutionary relationships and lineage-specific variation.

Methodology:

Neptune applies exact k-mer matching with mismatch accommodation, probabilistic models for loci discovery, and parallel computing to identify and extract loci from draft genome assemblies without requiring multiple sequence alignments.