Deciphering Biological Networks with Patterned Heterogeneous Measurements
Create initial F matrices using specific intergroup actions for networ...
Create F matrices using specific intergroup actions for network infere...
Reverse-engineer the network
Replace matrix values triangular lower part and by band for the upper ...
Replace matrix values triangular upper part and by band for the lower ...
Show methods
Summary methods
Replace matrix values by band.
Overview of a omics_array object
Analysing the network
Coerce a matrix into a omics_array object.
Create initial F matrices for cascade networks inference.
Create F matrices shaped for cascade networks inference.
A function to explore a dataset and cluster its rows.
A function to explore a dataset and cluster its rows.
Some basic criteria of comparison between actual and inferred network.
Choose the best cutoff
Dimension of the data
See the evolution of the network with change of cutoff
Simulates omicsarray data based on a given network.
Find the neighborhood of a set of nodes.
Methods for selecting genes
Generates a network.
Class "omics_array"
Class "omics_network"
Class "omics_predict"
Patterns: Deciphering Biological Networks with Patterned Heterogeneous...
Plot
Plot functions for the F matrices.
Returns the position of edges in the network
Methods for Function predict
Function to merge probesets
Makes the union between two omics_array objects.
Cluster a omics_array object: performs the clustering.
Cluster a omics_array object: determine optimal fuzzification paramete...
A modeling tool dedicated to biological network modeling (Bertrand and others 2020, <doi:10.1093/bioinformatics/btaa855>). It allows for single or joint modeling of, for instance, genes and proteins. It starts with the selection of the actors that will be the used in the reverse engineering upcoming step. An actor can be included in that selection based on its differential measurement (for instance gene expression or protein abundance) or on its time course profile. Wrappers for actors clustering functions and cluster analysis are provided. It also allows reverse engineering of biological networks taking into account the observed time course patterns of the actors. Many inference functions are provided and dedicated to get specific features for the inferred network such as sparsity, robust links, high confidence links or stable through resampling links. Some simulation and prediction tools are also available for cascade networks (Jung and others 2014, <doi:10.1093/bioinformatics/btt705>). Example of use with microarray or RNA-Seq data are provided.
Useful links