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LEANR

Implements the method described in [Gwinner et al., Network-based analysis of omics data: The LEAN method, Bioinformatics 2016]. 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 "?run.lean" in R prompt to do so) 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.

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Version

Install

install.packages('LEANR')

Monthly Downloads

27

Version

1.4.9

License

GPL-3

Maintainer

Frederik Gwinner

Last Published

November 12th, 2016

Functions in LEANR (1.4.9)

pvals_red

Gene p-value list used in unit tests
LEANR-package

Finds "local subnetworks" within an interaction network which show enrichment for differentially expressed genes
subnet.simulation

Simulate subnetworks
run.lean

Run the LEAN approach
write.ls.to.sif

Extract the "local subnetwork" around a given protein
gene.list.scores

Gene p-value list used in examples for function run.lean.fromdata
get.ls.info

Extract the genes of a "local subnetwork"" around a given protein
CCM.pvals

Gene p-value list derived from knock-out experiments of the three CCM genes
g2

igraph graph object used in examples for function run.lean.fromdata
g_red

igraph graph object used in unit tests
gene.annots

Annotation for STRING protein Ids