Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples
Abstract Background Malaria patients can have two or more haplotypes in their blood sample making it challenging to identify which haplotypes they carry. In addition, there are challenges in measuring the type and frequency of resistant haplotypes in populations. This study presents a novel statisti...
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ftdoajarticles:oai:doaj.org/article:ef44689570474e639e603e4b29541dc5 2023-05-15T15:06:10+02:00 Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples Gie Ken-Dror Pankaj Sharma 2021-07-01T00:00:00Z https://doi.org/10.1186/s12936-021-03841-9 https://doaj.org/article/ef44689570474e639e603e4b29541dc5 EN eng BMC https://doi.org/10.1186/s12936-021-03841-9 https://doaj.org/toc/1475-2875 doi:10.1186/s12936-021-03841-9 1475-2875 https://doaj.org/article/ef44689570474e639e603e4b29541dc5 Malaria Journal, Vol 20, Iss 1, Pp 1-11 (2021) Haplotype reconstruction Multiplicity of infection Single nucleotide polymorphisms Markov chain Monte Carlo Gibbs sampler algorithm Malaria Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2021 ftdoajarticles https://doi.org/10.1186/s12936-021-03841-9 2022-12-31T06:29:25Z Abstract Background Malaria patients can have two or more haplotypes in their blood sample making it challenging to identify which haplotypes they carry. In addition, there are challenges in measuring the type and frequency of resistant haplotypes in populations. This study presents a novel statistical method Gibbs sampler algorithm to investigate this issue. Results The performance of the algorithm is evaluated on simulated datasets consisting of patient blood samples characterized by their multiplicity of infection (MOI) and malaria genotype. The simulation used different resistance allele frequencies (RAF) at each Single Nucleotide Polymorphisms (SNPs) and different limit of detection (LoD) of the SNPs and the MOI. The Gibbs sampler algorithm presents higher accuracy among high LoD of the SNPs or the MOI, validated, and deals with missing MOI compared to previous related statistical approaches. Conclusions The Gibbs sampler algorithm provided robust results when faced with genotyping errors caused by LoDs and functioned well even in the absence of MOI data on individual patients. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 20 1 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Haplotype reconstruction Multiplicity of infection Single nucleotide polymorphisms Markov chain Monte Carlo Gibbs sampler algorithm Malaria Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
spellingShingle |
Haplotype reconstruction Multiplicity of infection Single nucleotide polymorphisms Markov chain Monte Carlo Gibbs sampler algorithm Malaria Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Gie Ken-Dror Pankaj Sharma Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples |
topic_facet |
Haplotype reconstruction Multiplicity of infection Single nucleotide polymorphisms Markov chain Monte Carlo Gibbs sampler algorithm Malaria Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background Malaria patients can have two or more haplotypes in their blood sample making it challenging to identify which haplotypes they carry. In addition, there are challenges in measuring the type and frequency of resistant haplotypes in populations. This study presents a novel statistical method Gibbs sampler algorithm to investigate this issue. Results The performance of the algorithm is evaluated on simulated datasets consisting of patient blood samples characterized by their multiplicity of infection (MOI) and malaria genotype. The simulation used different resistance allele frequencies (RAF) at each Single Nucleotide Polymorphisms (SNPs) and different limit of detection (LoD) of the SNPs and the MOI. The Gibbs sampler algorithm presents higher accuracy among high LoD of the SNPs or the MOI, validated, and deals with missing MOI compared to previous related statistical approaches. Conclusions The Gibbs sampler algorithm provided robust results when faced with genotyping errors caused by LoDs and functioned well even in the absence of MOI data on individual patients. |
format |
Article in Journal/Newspaper |
author |
Gie Ken-Dror Pankaj Sharma |
author_facet |
Gie Ken-Dror Pankaj Sharma |
author_sort |
Gie Ken-Dror |
title |
Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples |
title_short |
Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples |
title_full |
Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples |
title_fullStr |
Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples |
title_full_unstemmed |
Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples |
title_sort |
markov chain monte carlo gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples |
publisher |
BMC |
publishDate |
2021 |
url |
https://doi.org/10.1186/s12936-021-03841-9 https://doaj.org/article/ef44689570474e639e603e4b29541dc5 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 20, Iss 1, Pp 1-11 (2021) |
op_relation |
https://doi.org/10.1186/s12936-021-03841-9 https://doaj.org/toc/1475-2875 doi:10.1186/s12936-021-03841-9 1475-2875 https://doaj.org/article/ef44689570474e639e603e4b29541dc5 |
op_doi |
https://doi.org/10.1186/s12936-021-03841-9 |
container_title |
Malaria Journal |
container_volume |
20 |
container_issue |
1 |
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1766337827881091072 |