Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver

The predictive accuracy of mathematical models representing anything ranging from the meteorological to the biological system profoundly depends on the quality of model parameters derived from experimental data. Hence, robust sensitivity analysis (SA) of these critical model parameters aids in sifti...

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Autores principales:	Md Afsar Ali, S.A. Means, Harvey Ho, Jane Heffernan
Formato:	article
Lenguaje:	EN
Publicado:	KeAi Communications Co., Ltd. 2021
Materias:	Latin hypercube sampling Partial rank correlation coefficient (PRCC) Sobol method HBV Liver Infectious and parasitic diseases RC109-216
Acceso en línea:	https://doaj.org/article/0c9e885acd5e4b3f96313a84694d34df
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spelling	oai:doaj.org-article:0c9e885acd5e4b3f96313a84694d34df2021-11-04T04:36:38ZGlobal sensitivity analysis of a single-cell HBV model for viral dynamics in the liver2468-042710.1016/j.idm.2021.10.003https://doaj.org/article/0c9e885acd5e4b3f96313a84694d34df2021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2468042721000683https://doaj.org/toc/2468-0427The predictive accuracy of mathematical models representing anything ranging from the meteorological to the biological system profoundly depends on the quality of model parameters derived from experimental data. Hence, robust sensitivity analysis (SA) of these critical model parameters aids in sifting the influential from the negligible out of typically vast parameter regimes, thus illuminating key components of the system under study. We here move beyond traditional local sensitivity analysis to the adoption of global SA techniques. Partial rank correlation coefficient (PRCC) based on Latin hypercube sampling is compared with the variance-based Sobol method. We selected for this SA investigation an infection model for the hepatitis-B virus (HBV) that describes infection dynamics and clearance of HBV in the liver [Murray & Goyal, 2015]. The model tracks viral particles such as the tenacious and nearly ineradicable covalently closed circular DNA (cccDNA) embedded in infected nuclei and an HBV protein known as p36. Our application of these SA methods to the HBV model illuminates, especially over time, the quantitative relationships between cccDNA synthesis rate and p36 synthesis and export. Our results reinforce previous observations that the viral protein, p36, is by far the most influential factor for cccDNA replication. Moreover, both methods are capable of finding crucial parameters of the model. Though the Sobol method is independent of model structure (e.g., linearity and monotonicity) and well suited for SA, our results ensure that LHS-PRCC suffices for SA of a non-linear model if it is monotonic.Md Afsar AliS.A. MeansHarvey HoJane HeffernanKeAi Communications Co., Ltd.articleLatin hypercube samplingPartial rank correlation coefficient (PRCC)Sobol methodHBVLiverInfectious and parasitic diseasesRC109-216ENInfectious Disease Modelling, Vol 6, Iss , Pp 1220-1235 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Latin hypercube sampling Partial rank correlation coefficient (PRCC) Sobol method HBV Liver Infectious and parasitic diseases RC109-216
spellingShingle	Latin hypercube sampling Partial rank correlation coefficient (PRCC) Sobol method HBV Liver Infectious and parasitic diseases RC109-216 Md Afsar Ali S.A. Means Harvey Ho Jane Heffernan Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver
description	The predictive accuracy of mathematical models representing anything ranging from the meteorological to the biological system profoundly depends on the quality of model parameters derived from experimental data. Hence, robust sensitivity analysis (SA) of these critical model parameters aids in sifting the influential from the negligible out of typically vast parameter regimes, thus illuminating key components of the system under study. We here move beyond traditional local sensitivity analysis to the adoption of global SA techniques. Partial rank correlation coefficient (PRCC) based on Latin hypercube sampling is compared with the variance-based Sobol method. We selected for this SA investigation an infection model for the hepatitis-B virus (HBV) that describes infection dynamics and clearance of HBV in the liver [Murray & Goyal, 2015]. The model tracks viral particles such as the tenacious and nearly ineradicable covalently closed circular DNA (cccDNA) embedded in infected nuclei and an HBV protein known as p36. Our application of these SA methods to the HBV model illuminates, especially over time, the quantitative relationships between cccDNA synthesis rate and p36 synthesis and export. Our results reinforce previous observations that the viral protein, p36, is by far the most influential factor for cccDNA replication. Moreover, both methods are capable of finding crucial parameters of the model. Though the Sobol method is independent of model structure (e.g., linearity and monotonicity) and well suited for SA, our results ensure that LHS-PRCC suffices for SA of a non-linear model if it is monotonic.
format	article
author	Md Afsar Ali S.A. Means Harvey Ho Jane Heffernan
author_facet	Md Afsar Ali S.A. Means Harvey Ho Jane Heffernan
author_sort	Md Afsar Ali
title	Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver
title_short	Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver
title_full	Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver
title_fullStr	Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver
title_full_unstemmed	Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver
title_sort	global sensitivity analysis of a single-cell hbv model for viral dynamics in the liver
publisher	KeAi Communications Co., Ltd.
publishDate	2021
url	https://doaj.org/article/0c9e885acd5e4b3f96313a84694d34df
work_keys_str_mv	AT mdafsarali globalsensitivityanalysisofasinglecellhbvmodelforviraldynamicsintheliver AT sameans globalsensitivityanalysisofasinglecellhbvmodelforviraldynamicsintheliver AT harveyho globalsensitivityanalysisofasinglecellhbvmodelforviraldynamicsintheliver AT janeheffernan globalsensitivityanalysisofasinglecellhbvmodelforviraldynamicsintheliver
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Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver

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