Bryan Greenhouse

The paper analyzes whole genome data from Plasmodium falciparum isolates in Ethiopia to identify adaptive trajectories of antimalarial resistance evolution.

The paper characterizes the population structure and drug resistance of Plasmodium falciparum in Uganda and neighboring countries using whole-genome data, identifying key resistance-associated haplotypes.

PfPHAST is a streamlined amplicon sequencing panel for malaria genomic surveillance, offering better quality control and cost efficiency than MAD4HatTeR without sacrificing performance on shared targets.

The paper introduces a standardized format for storing phased targeted sequencing data and provides tools to create and manipulate this format.

This paper introduces a Bayesian framework for inferring transmission networks from polyclonal infections, demonstrating its application to Plasmodium falciparum with high precision and recall in simulations.

The paper identifies CXCR6⁺ CD127⁻ Tr1 cells as key regulators in Plasmodium falciparum infection, showing they balance immunity and parasite persistence.

This study investigates B cell and antibody responses to PfARMA, finding that IgM and IgG predominantly target the N-terminal IDR1 region, but these responses do not correlate with protection against malaria.

The paper introduces Aster, a statistical framework for accurately classifying antimalarial drug efficacy outcomes by accounting for complexity of infection and genotyping limitations.

The paper develops MAD4HatTeR, an amplicon sequencing panel and analysis pipeline for detecting Plasmodium falciparum diversity, resistance markers, and gene duplications/deletions, showing high sensitivity and reproducibility across settings.

MOIRE, a Bayesian R package, jointly infers allele frequencies, multiplicity of infection (MOI) and within-host relatedness from SNP or polyallelic malaria genotypes, yielding a panel-portable effective MOI.

Dcifer calculates genetic distance between polyclonal infections using IBD-based methods, showing higher statistical power than identity by state approaches and detecting related infections.

This study optimizes whole-genome sequencing of Plasmodium falciparum from low-density dried blood spots by evaluating DNA extraction, digestion, and amplification methods.

The paper develops a method to sequence microhaplotypes from Plasmodium falciparum heterozygomes, achieving high coverage, specificity, and sensitivity for detecting polyclonal infections.

This study evaluates genetic metrics for inferring malaria transmission intensity changes using a transmission model and finds one metric can predict prevalence with 0.055 mean absolute error.

The paper characterizes Plasmodium falciparum genetic diversity in Eswatini, finding high diversity despite low transmission, with no added value of diversity metrics in classifying imported vs. local infections.

The paper estimates the serial interval of Plasmodium falciparum malaria using mathematical models and empirical data, identifying factors that contribute to variability in transmission dynamics.