simpleConsensusCalculation: Simple calculation of a single consenus

In WGCNA: Weighted Correlation Network Analysis

Simple calculation of a single consenus

Description

This function calculates a single consensus from given individual data.

Usage

simpleConsensusCalculation(
  individualData, 
  consensusOptions, 
  verbose = 1, 
  indent = 0)

Arguments

individualData	Individual data from which the consensus is to be calculated. It can be either a list or a multiData structure in which each element is a numeric vector or array.
consensusOptions	A list of class ConsensusOptions that contains options for the consensus calculation. A suitable list can be obtained by calling function newConsensusOptions.
verbose	Integer level of verbosity of diagnostic messages. Zero means silent, higher values make the output progressively more and more verbose.
indent	Indentation for diagnostic messages. Zero means no indentation, each unit adds two spaces.

Details

Consensus is defined as the element-wise (also known as "parallel") quantile of of the individual data at probability given by the consensusQuantile element of consensusOptions.

Value

A numeric vector or array of the same dimensions as each element of individualData

Author(s)

Peter Langfelder

References

Consensus network analysis was originally described in Langfelder P, Horvath S. Eigengene networks for studying the relationships between co-expression modules. BMC Systems Biology 2007, 1:54 https://bmcsystbiol.biomedcentral.com/articles/10.1186/1752-0509-1-54

See Also

consensusCalculation for consensus calculation that can work with BlockwiseData and can calibrate data before calculating consensus.

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