inTB

inTB integrates clinical, socio-demographic, and molecular genotyping data to support epidemiological analysis of Mycobacterium tuberculosis.

Key Features:

• Data Integration: Integrates molecular genotyping data (SNP, MIRU-VNTR, RFLP, spoligotype) with clinical and socio-demographic variables.
• Strain Classification: Automatically classifies new isolates into strains based on an internal reference system.
• Phylogenetic Reconstruction: Generates phylogenetic trees for each genotyping method and a combined super tree that merges all methods.
• Analytical Outputs: Produces plots of various data types and allows export of datasets for external analyses.
• Filtered Subset Analysis: Generates trees and analyses from user-specified filtered subsets to cross-analyze molecular, clinical, and socio-demographic data.

Scientific Applications:

• Genetic Diversity Analysis: Investigates the genetic diversity of Mycobacterium tuberculosis across populations and regions.
• Resistance and Clinical Correlation: Links molecular genotype data to clinical and socio-demographic information to study the emergence and spread of multi-drug resistant TB.
• Evolutionary and Phenotypic Studies: Enables integrated analyses of how virulence and phenotypic traits evolve over time within epidemiological contexts.

Methodology:

Computational steps explicitly include integration of molecular (SNP, MIRU-VNTR, RFLP, spoligotype), clinical, and socio-demographic datasets; automatic strain classification using an internal reference system; generation of phylogenetic trees per genotyping method and a combined super tree; plotting of data; dataset export; and generation of trees from filtered data subsets.