genOr: Gene-oriented multiple module membership clustering

In jsieker/MultiMod: Expands WGCNA Clustering Analysis by Introducing a Pathway for Multiple Module Gene Assignment

Description

Allows for a gene-oriented, as opposed to a module-oriented, output format of multiple module clustering. The analysis of these two methods are extremely similar, but the outputs are useful for very different types of analyses.

Usage

genOr(threshold, kME, cutVal)

Arguments

threshold	A number between zero and one that serves as a cutoff of how well a gene must correlate with a certain module before it is considered part of that module in the analysis. A typical value is around 0.75, with more stringent analyses occuring around 0.90.
kME	The module eigenvalues outputted by WGCNA's 'blockwiseModules' or 'moduleEigengenes' functions.
cutVal	Allows the reduction of meaningless parts of the output. Defaults to true but can be turned to false for the sake of standardizing the output dataframe dimensions no matter the number of modules in the sample.

References

Langfelder P and Horvath S, WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 2008, 9:559 doi:10.1186/1471-2105-9-559

Peter Langfelder, Steve Horvath (2012). Fast R Functions for Robust Correlations and Hierarchical Clustering. Journal of Statistical Software, 46(11), 1-17. URL http://www.jstatsoft.org/v46/i11/.

jsieker/MultiMod documentation built on May 8, 2019, 1:02 p.m.