moire

moire estimates allele frequencies, multiplicity of infection (MOI), and within-host relatedness from polyallelic and SNP genetic data using a Bayesian approach, particularly for malaria parasite datasets where multiple related coinfecting strains may be present.

Key Features:

• Polyallelic and SNP data accommodation: moire handles both polyallelic data and single nucleotide polymorphism (SNP) data, making it applicable to diverse genotyping panels including microhaplotypes.
• Effective MOI (eMOI) metric: moire introduces a novel metric that integrates MOI and within-host relatedness to provide a robust, interpretable, and portable measure of genetic diversity that facilitates comparisons across settings with differing allele frequencies or genotyping panels.
• Within-host relatedness estimation: moire accounts for within-host relatedness among coinfecting strains, addressing a limitation of existing methods that rely solely on SNP data.
• Experimental error handling: moire incorporates experimental error into its Bayesian estimation framework for allele frequencies, MOI, and relatedness parameters.

Scientific Applications:

• Malaria parasite genetic analysis: moire enables estimation of allele frequencies, MOI, and within-host relatedness from malaria parasite genetic data to study parasite phenotypes, evolution, and transmission dynamics.
• Transmission dynamics assessment: moire detects heterogeneity in population mean MOI and mean relatedness across geographic regions, as demonstrated in a malaria study in Namibia revealing differences in transmission dynamics across health districts.
• Within-host diversity quantification: moire provides comprehensive insights into within-host diversity and population structure, accurately estimating MOI up to seven with moderate-sized panels of diverse loci.

Methodology:

moire implements a Bayesian approach to estimate allele frequencies, MOI, and within-host relatedness from genetic data subject to experimental error. The method was validated through extensive simulations and applied to real-world data from a malaria study in Namibia.