CoReg: Identify Co-regulators in transcription gene network

In LiLabAtVT/CoReg: Identification of co-regulators

Identify Co-regulators in transcription gene network

Description

This is the main function for identifying the co-regulators in transcription gene network

Usage

CoReg(g, gene.names = NULL, sim = "jaccard", minDegree = 1, deepSplit = 1, nThreads = 1)
## S3 method for class 'CoReg.result'
print(CoReg.result)
## S3 method for class 'CoReg.result'
summary(CoReg.result)

Arguments

g	The input transcription network. This should be an "igraph" object returned by the function "networkFromFile" or "networkFromEdgeList"
gene.names	Gene IDs on which CoReg will be run. If not set, gene.names will be decided solely by "minDegree"
sim	Similarity index for computing the similarity between genes. Available options are: "jaccard", "geometric", "invlogweighted". Default value is "jaccard".
minDegree	The minimum degree for genes that need similarity calculation. Genes with degree smaller than minDegree will not be computated and therefore will not be considered as co-regulator to any other genes
deepSplit	Parameter for dynamic tree cut algorithm. Can be a value in the range of 0 to 4. Higher value will produce more and smaller modules. Default value is 1.
nThreads	Number of threads to be used for similarity computation. Only valid when sim = "geometric".
CoReg.result	CoReg.result object

Details

This function takes an "igraph" object produced by "networkFromFile()" or "networkFromEdgeList()". The returned object includes the similarity matrix, rank and co-regulatory module assignment computed using the similarity index specified in sim argument. CoReg first calculates the pairwise similarity among all the genes, then performs hierarchical clustering and dynamic tree cut to obtain the final module assignment. See the following paper for more details about dynamic tree cut algorithm: Langfelder P, Zhang B, Horvath S (2007) Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R. Bioinformatics 2008 24(5):719-720.

Value

An object of class CoReg.result, a list including elements

module	a dataframe reporting the module ID for each gene
similarity_matrix	the similarity matrix for all the input genes
rank	the rank of similarity for all the gene pairs

Author(s)

Qi Song

References

Langfelder P, Zhang B, Horvath S (2007) Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R. Bioinformatics 2008 24(5):719-720.

See Also

networkFromFile networkFromEdgeList

Examples

data(athNet)
re <- CoReg(athNet)

# Display summary information for the identfied co-regulatory modules
summary(re)
print(re)

# Get the similarity matrix from the result
re$similarity_matrix

# Get the simialrity rank from the result
re$rank

# Get the module assignment from the result
re$module

LiLabAtVT/CoReg documentation built on May 8, 2022, 10:17 a.m.