Causal Network Analysis* will help you understand causal connections between diseases, genes and networks of upstream regulators.
The new Causal Network Analysis generates plausible regulatory networks which may explain the gene expression changes in your dataset. These novel upstream regulators control small hierarchical networks which do not require all the molecules to have direct connection to the dataset. Scoring criteria enable you to prioritize the most interesting and relevant hypothesis and quickly visualize the regulatory networks most closely associated with your disease or phenotype of interest.
Use Causal Network Analysis to generate novel hypothesis by uncovering hidden connections in upstream regulators to generate plausible causal networks which explain observed expression changes. Prioritize resulting hypothesis by molecule, disease, and/or phenotype of interest.