Function reference • Patterns

All functions
`CLL`	Expression data from healthy and malignant (chronic lymphocytic leukemia, CLL) human B-lymphocytes after B-cell receptor stimulation (GSE 39411 dataset)
`CascadeFinit()`	Create initial F matrices for cascade networks inference.
`CascadeFshape()`	Create F matrices shaped for cascade networks inference.
`IndicFinit()`	Create initial F matrices using specific intergroup actions for network inference.
`IndicFshape()`	Create F matrices using specific intergroup actions for network inference.
`M`	Simulated microarray.
`Net`	Simulated network for examples.
`Net_inf_PL`	Reverse-engineered network of the M and Net simulated data.
`Selection`	Selection of genes.
`analyze_network(<omics_network>)`	Analysing the network
`as.omics_array()`	Coerce a matrix into a omics_array object.
`clustExploration(<omics_array>)`	A function to explore a dataset and cluster its rows.
`clustInference(<omics_array>,<numeric>)`	A function to explore a dataset and cluster its rows.
`compare(<omics_network>,<omics_network>,<numeric>)`	Some basic criteria of comparison between actual and inferred network.
`cutoff(<omics_network>)`	Choose the best cutoff
`dim(<omics_array>)`	Dimension of the data
`doc`	Human transcription factors from HumanTFDB
`evolution(<omics_network>)`	See the evolution of the network with change of cutoff
`geneNeighborhood(<omics_network>)`	Find the neighborhood of a set of nodes.
`geneSelection(<omics_array>,<omics_array>,<numeric>)` `geneSelection(<list>,<list>,<numeric>)` `genePeakSelection(<omics_array>,<numeric>)`	Methods for selecting genes
`gene_expr_simulation(<omics_network>)`	Simulates omicsarray data based on a given network.
`head(<omics_array>)`	Overview of a omics_array object
`inference(<omics_array>)`	Reverse-engineer the network
`infos`	Details on some probesets of the affy_hg_u133_plus_2 platform.
`network`	A example of an inferred network (4 groups case).
`network2gp`	A example of an inferred cascade network (2 groups case).
`networkCascade`	A example of an inferred cascade network (4 groups case).
`network_random()`	Generates a network.
`omics_array-class`	Class `"omics_array"`
`omics_network-class`	Class `"omics_network"`
`omics_predict-class`	Class `"omics_predict"`
`plot(<omics_array>,<ANY>)` `plot(<omics_network>,<ANY>)` `plot(<omics_predict>,<ANY>)`	Plot
`plotF()`	Plot functions for the F matrices.
`position(<omics_network>)`	Returns the position of edges in the network
`predict(<omics_array>)`	Methods for Function `predict`
`probeMerge(<omics_array>)`	Function to merge probesets
`replaceBand()`	Replace matrix values by band.
`replaceDown()`	Replace matrix values triangular lower part and by band for the upper part.
`replaceUp()`	Replace matrix values triangular upper part and by band for the lower part.
`show(<omics_array>)` `show(<omics_network>)`	`Show` methods
`summary(<omics_array>)`	`Summary` methods
`unionOmics(<omics_array>,<omics_array>)`	Makes the union between two omics_array objects.
`unsupervised_clustering(<omics_array>,<numeric>,<numeric>)`	Cluster a omics_array object: performs the clustering.
`unsupervised_clustering_auto_m_c(<omics_array>)`	Cluster a omics_array object: determine optimal fuzzification parameter and number of clusters.

Reference

All functions