Journal
BIOSTATISTICS
Volume 16, Issue 2, Pages 240-251Publisher
OXFORD UNIV PRESS
DOI: 10.1093/biostatistics/kxu054
Keywords
Conditional independence; Directed acyclic graphs; Gaussian Markov models; Reversible jumps MCMC
Funding
- NIH [R01 CA132897, R01 CA158113-01]
- NIH/NCI [R01CA075981]
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We consider statistical inference for potentially heterogeneous patterns of association characterizing the expression of bio-molecular pathways across different biologic conditions. We discuss a modeling approach based on Gaussian-directed acyclic graphs and provide computational and methodological details needed for posterior inference. Our application finds motivation in reverse phase protein array data from a study on acute myeloid leukemia, where interest centers on contrasting refractory versus relapsed patients. We illustrate the proposed method through both synthetic and case study data.
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