A Factor Graph Nested Effects Model To Identify Networks from Genetic Perturbations
Figure 2
Structure of the factor graph for network inference.
The factor graph consists of three classes of variables (circles) and three classes of factors (squares). XeAr is a continuous observation of E-gene e's expression under ΔA and replicate r. YeA is the hidden state of E-gene e under ΔA, and is a discrete variable with domain {up, ∅, down}. φAB is the interaction between two S-genes A and B. Expression Factors model expression as a mixture of Gaussian distributions. Interaction Factors constrain E-gene states to the allowed regions shown in Figure 1C. Transitivity Factors constrain pair-wise interactions to form consistent triangles. The arrows labeled μ and μ′ are messages encoding local belief potentials on φAB and are propagated during factor graph inference.