Abstract
Biological regulatory pathways provide important information for target gene cancer therapy. Frequently, estimating the gene networks of two distinct patient groups is a worthwhile investigation. This paper proposes an approach, called jDAG, to the estimation of directed joint networks. It can identify common directed edges with joint data sets and distinct edges. In a simulation study, we show that the proposed jDAG outperforms existing methods although it does require longer computational times. We also present and discuss the example study of a breast cancer data set with ER + and ER-.
Original language | English |
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Pages (from-to) | 2793-2807 |
Number of pages | 15 |
Journal | Communications in Statistics: Simulation and Computation |
Volume | 50 |
Issue number | 9 |
DOIs | |
Publication status | Published - 2021 |
Keywords
- Bayesian network
- Drug response network
- Lasso estimation
- Probabilistic graphical model
- Structure equation model
- Unknown natural ordering
ASJC Scopus subject areas
- Statistics and Probability
- Modelling and Simulation