CytoBayesJ: Software tools for Bayesian analysis of cytogenetic radiation dosimetry data

Elizabeth Ainsbury; Volodymyr Vinnikov; Pedro Puig; Nataliya Maznyk; Kai Rothkamm; David C. Lloyd

doi:10.1016/j.mrgentox.2013.06.005

CytoBayesJ: Software tools for Bayesian analysis of cytogenetic radiation dosimetry data

Elizabeth Ainsbury^*, Volodymyr Vinnikov, Pedro Puig, Nataliya Maznyk, Kai Rothkamm, David C. Lloyd

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

A number of authors have suggested that a Bayesian approach may be most appropriate for analysis of cytogenetic radiation dosimetry data. In the Bayesian framework, probability of an event is described in terms of previous expectations and uncertainty. Previously existing, or prior, information is used in combination with experimental results to infer probabilities or the likelihood that a hypothesis is true. It has been shown that the Bayesian approach increases both the accuracy and quality assurance of radiation dose estimates. New software entitled CytoBayesJ has been developed with the aim of bringing Bayesian analysis to cytogenetic biodosimetry laboratory practice. CytoBayesJ takes a number of Bayesian or 'Bayesian like' methods that have been proposed in the literature and presents them to the user in the form of simple user-friendly tools, including testing for the most appropriate model for distribution of chromosome aberrations and calculations of posterior probability distributions. The individual tools are described in detail and relevant examples of the use of the methods and the corresponding CytoBayesJ software tools are given. In this way, the suitability of the Bayesian approach to biological radiation dosimetry is highlighted and its wider application encouraged by providing a user-friendly software interface and manual in English and Russian.

Original language	English
Pages (from-to)	184-191
Number of pages	8
Journal	Mutation Research - Genetic Toxicology and Environmental Mutagenesis
Volume	756
Issue number	1-2
DOIs	https://doi.org/10.1016/j.mrgentox.2013.06.005
Publication status	Published - 30 May 2013

Bibliographical note

Funding Information:
This work was funded by the UK Royal Society , under project number JP080153 , and the NIHR Centre for Research in Health Protection at the Health Protection Agency. Cytogenetic data in radiotherapy patients were collected as part of the IMR project NAMN 01.11, supported by the National Academy of Medical Science of Ukraine ; project state registration no. 0111U002039 . The work carried out at UAB was funded by the grant MTM2012-31118 . The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the UK Department of Health or the National Academy of Medical Science of Ukraine.

Keywords

Bayesian
Biological dosimetry (biodosimetry)
Hermite
Negative binomial
Neyman type-A
Radiation cytogenetics

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10.1016/j.mrgentox.2013.06.005

Cite this

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abstract = "A number of authors have suggested that a Bayesian approach may be most appropriate for analysis of cytogenetic radiation dosimetry data. In the Bayesian framework, probability of an event is described in terms of previous expectations and uncertainty. Previously existing, or prior, information is used in combination with experimental results to infer probabilities or the likelihood that a hypothesis is true. It has been shown that the Bayesian approach increases both the accuracy and quality assurance of radiation dose estimates. New software entitled CytoBayesJ has been developed with the aim of bringing Bayesian analysis to cytogenetic biodosimetry laboratory practice. CytoBayesJ takes a number of Bayesian or 'Bayesian like' methods that have been proposed in the literature and presents them to the user in the form of simple user-friendly tools, including testing for the most appropriate model for distribution of chromosome aberrations and calculations of posterior probability distributions. The individual tools are described in detail and relevant examples of the use of the methods and the corresponding CytoBayesJ software tools are given. In this way, the suitability of the Bayesian approach to biological radiation dosimetry is highlighted and its wider application encouraged by providing a user-friendly software interface and manual in English and Russian.",

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note = "Funding Information: This work was funded by the UK Royal Society , under project number JP080153 , and the NIHR Centre for Research in Health Protection at the Health Protection Agency. Cytogenetic data in radiotherapy patients were collected as part of the IMR project NAMN 01.11, supported by the National Academy of Medical Science of Ukraine ; project state registration no. 0111U002039 . The work carried out at UAB was funded by the grant MTM2012-31118 . The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the UK Department of Health or the National Academy of Medical Science of Ukraine.",

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CytoBayesJ: Software tools for Bayesian analysis of cytogenetic radiation dosimetry data

Abstract

Bibliographical note

Keywords

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