SpolLineages

SpolLineages predicts Mycobacterium tuberculosis complex (MTBC) spoligotype families from spoligotyping and MIRU‑VNTR patterns to support lineage assignment for epidemiological and evolutionary analyses.

Key Features:

• Methodological Diversity: Implements SITVIT2 binary rules, RuleTB refined rules, decision tree classifiers, and evolutionary algorithms for lineage prediction from spoligotyping and MIRU‑VNTR data.
• Data-Driven Approaches: Incorporates a decision tree classifier that uses data transformation techniques and an evolutionary algorithm that identifies simple rules through binary masks.
• Performance and Efficiency: Comparative analyses with existing methods report reduced runtime while maintaining high accuracy in spoligotype family prediction.

Scientific Applications:

• Lineage distribution and evolution: Enables analysis of MTBC lineage distribution and evolutionary relationships based on spoligotype families.
• Epidemiological surveillance: Supports surveillance studies by assigning spoligotype families for population-level monitoring of TB.
• Outbreak investigation: Assists outbreak tracking through rapid family prediction from spoligotyping and MIRU‑VNTR patterns.
• Database integration: Integrates with the SITVIT2 spoligotype repository to leverage curated spoligotype data for assignment and comparison.

Methodology:

Transforms spoligotyping patterns into formats suitable for decision tree classifiers and evolutionary algorithms, applies SITVIT2 binary rules and RuleTB refined rules, and uses an evolutionary algorithm that optimizes rule sets via iterative binary mask applications.