An integrative statistical model for inferring strain admixture within clinical Plasmodium falciparum isolates

TL;DR

This paper introduces a new statistical model that accurately infers the number of Plasmodium falciparum strains and their admixture proportions within clinical samples using whole-genome sequencing data, improving over previous methods.

Contribution

The paper presents a novel statistical model for inferring strain number and admixture proportions in Plasmodium falciparum from genome data, enhancing analysis accuracy.

Findings

Model significantly outperforms simpler approaches in most samples

Provides detailed estimates of strain proportions and admixture levels

Offers insights into within-host parasite diversity

Abstract

Since the arrival of genetic typing methods in the late 1960's, researchers have puzzled at the clinical consequence of observed strain mixtures within clinical isolates of Plasmodium falciparum. We present a new statistical model that infers the number of strains present and the amount of admixture with the local population (panmixia) using whole-genome sequence data. The model provides a rigorous statistical approach to inferring these quantities as well as the proportions of the strains within each sample. Applied to 168 samples of whole-genome sequence data from northern Ghana, the model provides significantly improvement fit over models implementing simpler approaches to mixture for a large majority (129/168) of samples. We discuss the possible uses of this model as a window into within-host selection for clinical and epidemiological studies and outline possible means for experimental validation.