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Gaussian Bayesian network comparisons with graph ordering unknown

Gaussian Bayesian network comparisons with graph ordering unknown
Gaussian Bayesian network comparisons with graph ordering unknown
A Bayesian approach is proposed that unifies Gaussian Bayesian network constructions and comparisons between two networks (identical or differential) for data with graph ordering unknown. When sampling graph ordering, to escape from local maximums, an adjusted single queue equi-energy algorithm is applied. The conditional posterior probability mass function for network differentiation is derived and its asymptotic proposition is theoretically assessed. Simulations are used to demonstrate the approach and compare with existing methods. Based on epigenetic data at a set of DNA methylation sites (CpG sites), the proposed approach is further examined on its ability to detect network differentiations. Findings from theoretical assessment, simulations, and real data applications support the efficacy and efficiency of the proposed method for network comparisons.
Bayesian methods, DNA methylation, Differential Gaussian Bayesian network, Ordering, Single Queue Equi-Energy, Variable selections
0167-9473
Zhang, Hongmei
9f774048-54d6-4321-a252-3887b2c76db0
Haung, Xianzheng
98d97615-137e-4af8-a113-ae7e540187ef
Han, Shengtong
eee0c306-f700-4012-b9de-97b900034835
Rezwan, Faisal I
203f8f38-1f5d-485b-ab11-c546b4276338
Karmaus, Wilfried
281d0e53-6b5d-4d38-9732-3981b07cd853
Arshad, Syed
917e246d-2e60-472f-8d30-94b01ef28958
Holloway, John
4bbd77e6-c095-445d-a36b-a50a72f6fe1a
Zhang, Hongmei
9f774048-54d6-4321-a252-3887b2c76db0
Haung, Xianzheng
98d97615-137e-4af8-a113-ae7e540187ef
Han, Shengtong
eee0c306-f700-4012-b9de-97b900034835
Rezwan, Faisal I
203f8f38-1f5d-485b-ab11-c546b4276338
Karmaus, Wilfried
281d0e53-6b5d-4d38-9732-3981b07cd853
Arshad, Syed
917e246d-2e60-472f-8d30-94b01ef28958
Holloway, John
4bbd77e6-c095-445d-a36b-a50a72f6fe1a

Zhang, Hongmei, Haung, Xianzheng, Han, Shengtong, Rezwan, Faisal I, Karmaus, Wilfried, Arshad, Syed and Holloway, John (2021) Gaussian Bayesian network comparisons with graph ordering unknown. Computational Statistics & Data Analysis, 157, [107156]. (doi:10.1016/j.csda.2020.107156).

Record type: Article

Abstract

A Bayesian approach is proposed that unifies Gaussian Bayesian network constructions and comparisons between two networks (identical or differential) for data with graph ordering unknown. When sampling graph ordering, to escape from local maximums, an adjusted single queue equi-energy algorithm is applied. The conditional posterior probability mass function for network differentiation is derived and its asymptotic proposition is theoretically assessed. Simulations are used to demonstrate the approach and compare with existing methods. Based on epigenetic data at a set of DNA methylation sites (CpG sites), the proposed approach is further examined on its ability to detect network differentiations. Findings from theoretical assessment, simulations, and real data applications support the efficacy and efficiency of the proposed method for network comparisons.

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BayesianNetworkComparisonCSDAR1 - Accepted Manuscript
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Accepted/In Press date: 7 December 2020
e-pub ahead of print date: 26 December 2020
Published date: May 2021
Additional Information: Funding Information: The research work of H Zhang, W Karmaus, H Arshad, and J Holloway was supported by NIH/NIAID, USA R01AI121226 (MPI: Zhang, Holloway). The work of FI Rezwan was supported by the Ageing Lungs in European Cohorts (ALEC) Study, European Union (EU Horizon 2020, Grant Number 633212 ). The authors are thankful to the High Performance Computing facility at the University of Memphis. Funding Information: The research work of H Zhang, W Karmaus, H Arshad, and J Holloway was supported by NIH/NIAID, USAR01AI121226 (MPI: Zhang, Holloway). The work of FI Rezwan was supported by the Ageing Lungs in European Cohorts (ALEC) Study, European Union (EU Horizon 2020, Grant Number 633212). The authors are thankful to the High Performance Computing facility at the University of Memphis. Publisher Copyright: © 2020 Elsevier B.V.
Keywords: Bayesian methods, DNA methylation, Differential Gaussian Bayesian network, Ordering, Single Queue Equi-Energy, Variable selections

Identifiers

Local EPrints ID: 445640
URI: http://eprints.soton.ac.uk/id/eprint/445640
ISSN: 0167-9473
PURE UUID: cf055b69-7aff-45dc-9e23-f51751dbcbfd
ORCID for Faisal I Rezwan: ORCID iD orcid.org/0000-0001-9921-222X
ORCID for John Holloway: ORCID iD orcid.org/0000-0001-9998-0464

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Date deposited: 05 Jan 2021 17:30
Last modified: 17 Mar 2024 06:10

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Contributors

Author: Hongmei Zhang
Author: Xianzheng Haung
Author: Shengtong Han
Author: Faisal I Rezwan ORCID iD
Author: Wilfried Karmaus
Author: Syed Arshad
Author: John Holloway ORCID iD

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