Empowering differential networks using Bayesian analysis.
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ABSTRACT:
SUBMITTER: Smith J
PROVIDER: S-EPMC8789149 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
Empowering differential networks using Bayesian analysis.
Smith Jarod J Arashi Mohammad M Bekker Andriëtte A
PloS one 20220125 1
Differential networks (DN) are important tools for modeling the changes in conditional dependencies between multiple samples. A Bayesian approach for estimating DNs, from the classical viewpoint, is introduced with a computationally efficient threshold selection for graphical model determination. The algorithm separately estimates the precision matrices of the DN using the Bayesian adaptive graphical lasso procedure. Synthetic experiments illustrate that the Bayesian DN performs exceptionally we ...[more]
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