Malaria haplotype frequency estimation.

Détails

ID Serval
serval:BIB_A0FED704BD9B
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Malaria haplotype frequency estimation.
Périodique
Statistics in Medicine
Auteur(s)
Wigger L., Vogt J.E., Roth V.
ISSN
1097-0258 (Electronic)
ISSN-L
0277-6715
Statut éditorial
Publié
Date de publication
2013
Volume
32
Numéro
21
Pages
3737-3751
Langue
anglais
Résumé
We present a Bayesian approach for estimating the relative frequencies of multi-single nucleotide polymorphism (SNP) haplotypes in populations of the malaria parasite Plasmodium falciparum by using microarray SNP data from human blood samples. Each sample comes from a malaria patient and contains one or several parasite clones that may genetically differ. Samples containing multiple parasite clones with different genetic markers pose a special challenge. The situation is comparable with a polyploid organism. The data from each blood sample indicates whether the parasites in the blood carry a mutant or a wildtype allele at various selected genomic positions. If both mutant and wildtype alleles are detected at a given position in a multiply infected sample, the data indicates the presence of both alleles, but the ratio is unknown. Thus, the data only partially reveals which specific combinations of genetic markers (i.e. haplotypes across the examined SNPs) occur in distinct parasite clones. In addition, SNP data may contain errors at non-negligible rates. We use a multinomial mixture model with partially missing observations to represent this data and a Markov chain Monte Carlo method to estimate the haplotype frequencies in a population. Our approach addresses both challenges, multiple infections and data errors.
Mots-clé
malaria, multiple infection, haplotypes, frequency estimation, Bayesian mixture model, Gibbs sampling
Pubmed
Web of science
Création de la notice
12/09/2013 18:21
Dernière modification de la notice
20/08/2019 16:07
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