THD

THD calculates time-scaled haplotypic density to quantify the epidemic success of individual pathogen isolates from genetic distance metrics in R.

Key Features:

• Individual-Based Success Index: Computes a time-scaled haplotypic density-derived index of epidemic success for each pathogen isolate.
• Integration with Multivariate Models: Produces isolate-level success indices that serve as response variables in multivariate regression models to identify predictors of epidemic success.
• Application to Genomic Data: Leverages large-scale genomic datasets and correlates genetic data with ancillary parameters such as drug resistance profiles (e.g., rifampicin, fluoroquinolones).
• Control of Confounding: Enables analyses that account for biases from population structure and geographic distribution when comparing isolate success.

Scientific Applications:

• MDR Mycobacterium tuberculosis Beijing: THD analyses implicated rifampicin resistance as a significant driver of this epidemic.
• Staphylococcus aureus ST8/USA300 (MRSA): THD identified fluoroquinolone resistance as a key factor associated with epidemic success in ST8/USA300.
• Salmonella Typhi H58 and non-H58: THD found fluoroquinolone resistance to be associated with reduced epidemic success in both H58 and non-H58 S. Typhi strains.

Methodology:

Calculates time-scaled haplotypic densities from genetic distance metrics, assigns an epidemic success index to each isolate, and uses those indices as response variables in multivariate regression models while accounting for population structure and geographic distribution.