Finds "local subnetworks" within an interaction network which show enrichment for differentially expressed genes
Implements the method described in "Network-based analysis of omics data: The LEAN method". Given a protein interaction network and a list of p-values describing a measure of interest (as e.g. differential gene expression) this method computes an enrichment p-value for the protein neighborhood of each gene and compares it to a background distribution of randomly drawn p-values. The resulting scores are corrected for multiple testing and significant hits are returned in tabular format.
See help page of run.lean for a more detailed description of how to use this package. Type vignette("CCM-data") for an example showing the application of LEAN to the CCM knockout data set discussed in the paper. Type vignette("subnet-sim") for an example showing the application of LEAN to simulated subnetwork data discussed in the paper.
Maintainer: Frederik Gwinner <email@example.com>
Gwinner et al., Network-based analysis of omics data: The LEAN method, Bioinformatics 2016
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