MalReBay is an R package designed to analyze genotyping data from Therapeutic Efficacy Studies (TES) and classify recurrent malaria parasite infections. It determines the posterior probability that a given infection is a recrudescence (a treatment failure) versus a new infection. Unlike simple allele-matching methods, MalReBay implements a Bayesian algorithm, solved using a Markov Chain Monte Carlo (MCMC) engine, to provide a robust probabilistic classification for each sample.
It supports analysis of both traditional length-polymorphic markers (microsatellites, msp1, msp2, and glurp) and modern amplicon sequencing data. For length-polymorphic data (microsatellites, msp), it employs a distance-based likelihood model that accounts for PCR stutter and scoring errors. For amplicon sequencing data, it uses an exact-match categorical model, which is suitable for discrete haplotypes. The framework robustly handles polyclonal infections and imputes missing genotypes as part of the MCMC sampling, providing a powerful tool for modern TES data analysis.
You can install the development version of MalReBay from GitHub with:
remotes::install_github("SwissTPH/MalReBay")