Exact vs. Approximate Computation: Reconciling Different Estimates of Mycobacterium tuberculosis Epidemiological Parameters

Exact computational methods for inference in population genetics are intuitively preferable to approximate analyses. We reconcile two starkly different estimates of the reproductive number of tuberculosis from previous studies that used the same genotyping data and underlying model. This demonstrate...

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Detalles Bibliográficos
Autores principales: Aandahl, R. Zachariah, Stadler, Tanja, Sisson, Scott A., Tanaka, Mark M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2014
Materias:
Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3982679/
https://www.ncbi.nlm.nih.gov/pubmed/24496011
http://dx.doi.org/10.1534/genetics.113.158808
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author Aandahl, R. Zachariah
Stadler, Tanja
Sisson, Scott A.
Tanaka, Mark M.
author_facet Aandahl, R. Zachariah
Stadler, Tanja
Sisson, Scott A.
Tanaka, Mark M.
author_sort Aandahl, R. Zachariah
collection PubMed
description Exact computational methods for inference in population genetics are intuitively preferable to approximate analyses. We reconcile two starkly different estimates of the reproductive number of tuberculosis from previous studies that used the same genotyping data and underlying model. This demonstrates the value of approximate analyses in validating exact methods.
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spelling pubmed-39826792015-04-01 Exact vs. Approximate Computation: Reconciling Different Estimates of Mycobacterium tuberculosis Epidemiological Parameters Aandahl, R. Zachariah Stadler, Tanja Sisson, Scott A. Tanaka, Mark M. Genetics Note Exact computational methods for inference in population genetics are intuitively preferable to approximate analyses. We reconcile two starkly different estimates of the reproductive number of tuberculosis from previous studies that used the same genotyping data and underlying model. This demonstrates the value of approximate analyses in validating exact methods. Genetics Society of America 2014-04 2014-02-04 /pmc/articles/PMC3982679/ /pubmed/24496011 http://dx.doi.org/10.1534/genetics.113.158808 Text en Copyright © 2014 Aandahl et al. Available freely online through the author-supported open access option. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Note
Aandahl, R. Zachariah
Stadler, Tanja
Sisson, Scott A.
Tanaka, Mark M.
Exact vs. Approximate Computation: Reconciling Different Estimates of Mycobacterium tuberculosis Epidemiological Parameters
title Exact vs. Approximate Computation: Reconciling Different Estimates of Mycobacterium tuberculosis Epidemiological Parameters
title_full Exact vs. Approximate Computation: Reconciling Different Estimates of Mycobacterium tuberculosis Epidemiological Parameters
title_fullStr Exact vs. Approximate Computation: Reconciling Different Estimates of Mycobacterium tuberculosis Epidemiological Parameters
title_full_unstemmed Exact vs. Approximate Computation: Reconciling Different Estimates of Mycobacterium tuberculosis Epidemiological Parameters
title_short Exact vs. Approximate Computation: Reconciling Different Estimates of Mycobacterium tuberculosis Epidemiological Parameters
title_sort exact vs. approximate computation: reconciling different estimates of mycobacterium tuberculosis epidemiological parameters
topic Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3982679/
https://www.ncbi.nlm.nih.gov/pubmed/24496011
http://dx.doi.org/10.1534/genetics.113.158808
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