regulatory networks

This package implements methods and an evaluation framework to infer differential co-expression/association networks. Various methods are implemented and can be evaluated using simulated datasets. Inference of differential co-expression networks can allow identification of networks that are altered between two conditions (e.g., health and disease).

This talk presents a simple mathematical model of gene regulation used to simulate expression data to evaluate differential co-expression network inference methods.

dcanr is a method that helps infer differential regulatory networks from high-througput ‘omics data