Builds the relevance correlation network

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Description

This function builds the relevance correlation network for the genes in the model pathway signature in the given data set.

Usage

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BuildRN(data.m, sign.v, fdr)

Arguments

data.m

Data matrix (numeric). Rows label features (genes), columns label samples. It is assumed that the number of features is much larger than the number of samples. Rownames must be a valid gene or probe identifier.

sign.v

Model pathway signature vector (numeric). Elements correspond to the regulatory weights, i.e the sign indicates if up or downregulated. Names of sign.v must be a gene name (probe) identifier which must match the gene (probe) identifier used for the rows of data.m.

fdr

Desired false discovery rate (numeric) which determines the allowed number of false positives in the relevance network. The default value is 0.000001. Since typically model signatures may contain on the order of 100 genes, this amounts to constructing a relevance network on the order of 10000 edges (pairwise correlations). Using a Bonferroni correction, this leads to a P-value threshold of approx. 1e-6 to 1e-7. This parameter is tunable, so choosing a number of different thresholds may be advisable.

Value

A list with following entries:

adj

Adjacency matrix of inferred relevance network

s

Model signature vector in data

sd

Gene signature data matrix

c

Correlations between signature genes

d

Data matrix

rep.idx

Indices of the genes in signature which could be found in data matrix

Author(s)

Andrew E Teschendorff, Yan Jiao

References

Jiao Y, Lawler K, Patel GS, Purushotham A, Jones AF, Grigoriadis A, Ng T, Teschendorff AE. (2011) Denoising algorithm based on relevance network topology improves molecular pathway activity inference. BMC Bioinformatics 12:403.

Teschendorff AE, Gomez S, Arenas A, El-Ashry D, Schmidt M, et al. (2010) Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules. BMC Cancer 10:604.

Examples

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data(dataDART)
rn.o <- BuildRN(dataDART$data, dataDART$sign, fdr=0.000001)
## See ?DoDART and vignette('DART') for further examples.