Patterns: Deciphering Biological Networks with Patterned Heterogeneous (multiOmics) Measurements
The Patterns package is a modelling tool dedicated to biological network modelling.
It is designed to work with patterned data. Famous examples of problems related to patterned data are:
* recovering signals in networks after a stimulation (cascade network reverse engineering),
* analysing periodic signals.
It allows for single or joint modelling of, for instance, genes and proteins.
It provides tools to select relevant actors to be used in the reverse engineering step -based on their differential effects (e.g. gene expression or protein abundance) or on their time course profile-.
It performs reverse engineering based on the observed time course patterns of the actors.
It provides many inference functions that are dedicated to getting specific features for the inferred network such as sparsity, robust links, high confidence links or stable through resampling links. They can be based on weighted or unweighted versions of lasso, spls, elastic net, stability selection, robust lasso, selectboost, from the selectboost package.
Some simulation and prediction tools are also available for cascade networks.
Examples of use with microarray or RNA-Seq data are provided.