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ushr: Understanding suppression of HIV in R
BACKGROUND: HIV/AIDS is responsible for the deaths of one million people every year. Although mathematical modeling has provided many insights into the dynamics of HIV infection, there is still a lack of accessible tools for researchers unfamiliar with modeling techniques to apply them to their own...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014720/ https://www.ncbi.nlm.nih.gov/pubmed/32046642 http://dx.doi.org/10.1186/s12859-020-3389-x |
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author | Morris, Sinead E Dziobek-Garrett, Luise Yates, Andrew J collaboration with the EPIICAL Consortium, in |
author_facet | Morris, Sinead E Dziobek-Garrett, Luise Yates, Andrew J collaboration with the EPIICAL Consortium, in |
author_sort | Morris, Sinead E |
collection | PubMed |
description | BACKGROUND: HIV/AIDS is responsible for the deaths of one million people every year. Although mathematical modeling has provided many insights into the dynamics of HIV infection, there is still a lack of accessible tools for researchers unfamiliar with modeling techniques to apply them to their own clinical data. RESULTS: Here we present ushr, a free and open-source R package that models the decline of HIV during antiretroviral treatment (ART) using a popular mathematical framework. ushr can be applied to longitudinal data of viral load measurements, and provides processing tools to prepare it for computational analysis. By mathematically fitting the data, important biological parameters can then be estimated, including the lifespans of short and long-lived infected cells, and the time to reach viral suppression below a defined detection threshold. The package also provides visualization and summary tools for fast assessment of model results. CONCLUSIONS: ushr enables researchers without a strong mathematical or computational background to model the dynamics of HIV using longitudinal clinical data. Increasing accessibility to such methods may facilitate quantitative analysis across a broader range of independent studies, so that greater insights on HIV infection and treatment dynamics may be gained. |
format | Online Article Text |
id | pubmed-7014720 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70147202020-02-20 ushr: Understanding suppression of HIV in R Morris, Sinead E Dziobek-Garrett, Luise Yates, Andrew J collaboration with the EPIICAL Consortium, in BMC Bioinformatics Software BACKGROUND: HIV/AIDS is responsible for the deaths of one million people every year. Although mathematical modeling has provided many insights into the dynamics of HIV infection, there is still a lack of accessible tools for researchers unfamiliar with modeling techniques to apply them to their own clinical data. RESULTS: Here we present ushr, a free and open-source R package that models the decline of HIV during antiretroviral treatment (ART) using a popular mathematical framework. ushr can be applied to longitudinal data of viral load measurements, and provides processing tools to prepare it for computational analysis. By mathematically fitting the data, important biological parameters can then be estimated, including the lifespans of short and long-lived infected cells, and the time to reach viral suppression below a defined detection threshold. The package also provides visualization and summary tools for fast assessment of model results. CONCLUSIONS: ushr enables researchers without a strong mathematical or computational background to model the dynamics of HIV using longitudinal clinical data. Increasing accessibility to such methods may facilitate quantitative analysis across a broader range of independent studies, so that greater insights on HIV infection and treatment dynamics may be gained. BioMed Central 2020-02-11 /pmc/articles/PMC7014720/ /pubmed/32046642 http://dx.doi.org/10.1186/s12859-020-3389-x Text en © The Author(s) 2020 Open Access This article is 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 you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Morris, Sinead E Dziobek-Garrett, Luise Yates, Andrew J collaboration with the EPIICAL Consortium, in ushr: Understanding suppression of HIV in R |
title | ushr: Understanding suppression of HIV in R |
title_full | ushr: Understanding suppression of HIV in R |
title_fullStr | ushr: Understanding suppression of HIV in R |
title_full_unstemmed | ushr: Understanding suppression of HIV in R |
title_short | ushr: Understanding suppression of HIV in R |
title_sort | ushr: understanding suppression of hiv in r |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014720/ https://www.ncbi.nlm.nih.gov/pubmed/32046642 http://dx.doi.org/10.1186/s12859-020-3389-x |
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