coiaf: Directly estimating complexity of infection with allele frequencies.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
Jun 2023
Jun 2023
Historique:
received:
23
05
2022
accepted:
01
05
2023
revised:
29
06
2023
medline:
3
7
2023
pubmed:
9
6
2023
entrez:
9
6
2023
Statut:
epublish
Résumé
In malaria, individuals are often infected with different parasite strains. The complexity of infection (COI) is defined as the number of genetically distinct parasite strains in an individual. Changes in the mean COI in a population have been shown to be informative of changes in transmission intensity with a number of probabilistic likelihood and Bayesian models now developed to estimate the COI. However, rapid, direct measures based on heterozygosity or FwS do not properly represent the COI. In this work, we present two new methods that use easily calculated measures to directly estimate the COI from allele frequency data. Using a simulation framework, we show that our methods are computationally efficient and comparably accurate to current approaches in the literature. Through a sensitivity analysis, we characterize how the distribution of parasite densities, the assumed sequencing depth, and the number of sampled loci impact the bias and accuracy of our two methods. Using our developed methods, we further estimate the COI globally from Plasmodium falciparum sequencing data and compare the results against the literature. We show significant differences in the estimated COI globally between continents and a weak relationship between malaria prevalence and COI.
Identifiants
pubmed: 37294835
doi: 10.1371/journal.pcbi.1010247
pii: PCOMPBIOL-D-22-00780
pmc: PMC10310041
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1010247Subventions
Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom
Organisme : NIAID NIH HHS
ID : R01 AI139520
Pays : United States
Informations de copyright
Copyright: © 2023 Paschalidis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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