correlationPreservation: Preservation of eigengene correlations
In nosarcasm/WGCNA: Weighted Correlation Network Analysis

Description Usage Arguments Details Value Author(s) References See Also

Calculates a summary measure of preservation of eigengene correlations across data sets

1	correlationPreservation(multiME, setLabels, excludeGrey = TRUE, greyLabel = "grey")

`multiME`	consensus module eigengenes in a multi-set format. A vector of lists with one list corresponding to each set. Each list must contain a component `data` that is a data frame whose columns are consensus module eigengenes.
`setLabels`	names to be used for the sets represented in `multiME`.
`excludeGrey`	logical: exclude the 'grey' eigengene from preservation measure?
`greyLabel`	module label corresponding to the 'grey' module. Usually this will be the character string `"grey"` if the labels are colors, and the number 0 if the labels are numeric.

The function calculates the preservation of correlation of each eigengene with all other eigengenes (optionally except the 'grey' eigengene) in all pairs of sets.

A data frame whose rows correspond to consensus module eigengenes given in the input multiME, and columns correspond to all possible set comparisons. The two sets compared in each column are indicated in the column name.

Peter Langfelder

Langfelder P, Horvath S (2007) Eigengene networks for studying the relationships between co-expression modules. BMC Systems Biology 2007, 1:54

multiSetMEs and modulecheckSets in package moduleColor for more on eigengenes and the multi-set format

nosarcasm/WGCNA documentation built on May 28, 2019, 1:01 p.m.