consensusMEDissimilarity: Consensus dissimilarity of module eigengenes.

In WGCNA: Weighted Correlation Network Analysis

Consensus dissimilarity of module eigengenes.

Description

Calculates consensus dissimilarity (1-cor) of given module eigengenes realized in several sets.

Usage

consensusMEDissimilarity(MEs, useAbs = FALSE, useSets = NULL, method = "consensus")

Arguments

MEs	Module eigengenes of the same modules in several sets.
useAbs	Controls whether absolute value of correlation should be used instead of correlation in the calculation of dissimilarity.
useSets	If the consensus is to include only a selection of the given sets, this vector (or scalar in the case of a single set) can be used to specify the selection. If NULL, all sets will be used.
method	A character string giving the method to use. Allowed values are (abbreviations of) "consensus" and "majority". The consensus dissimilarity is calculated as the minimum of given set dissimilarities for "consensus" and as the average for "majority".

Details

This function calculates the individual set dissimilarities of the given eigengenes in each set, then takes the (parallel) maximum or average over all sets. For details on the structure of imput data, see checkSets.

Value

A dataframe containing the matrix of dissimilarities, with names and rownames set appropriately.

Author(s)

Peter Langfelder, [e-mail]

See Also

checkSets

WGCNA documentation built on Sept. 18, 2024, 5:08 p.m.