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Description

Finds "Local Subnetworks" Within an Interaction Network which Show Enrichment for Differentially E….

Implements the method described in "Network-based analysis of omics data: The LEAN method" [Gwinner Boulday (2016) <DOI:10.1093/bioinformatics/btw676>] 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.

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.

Metadata

Version

1.4.9

License

Unknown

Platforms (75)

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    FreeBSD
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