newConsensusOptions: Create a list holding consensus calculation options.
In nosarcasm/WGCNA: Weighted Correlation Network Analysis

Description Usage Arguments Value Author(s)

This function creates a list of class ConsensusOptions that holds options for consensus calculations. This list holds options for a single-level analysis.

newConsensusOptions(
      calibration = c("full quantile", "single quantile", "none"),

      # Simple quantile scaling options
      calibrationQuantile = 0.95,
      sampleForCalibration = TRUE, 
      sampleForCalibrationFactor = 1000,

      # Consensus definition
      consensusQuantile = 0,
      useMean = FALSE,
      setWeights = NULL,
      # Name to prevent clashing of files
      analysisName = "")

`calibration`	Calibration method. One of `"full quantile", "single quantile", "none"` (or a unique abbreviation of one of them).
`calibrationQuantile`	if `calibration` is `"single quantile"`, input data to a consensus calculation will be scaled such that their `calibrationQuantile` quantiles will agree.
`sampleForCalibration`	if `TRUE`, calibration quantiles will be determined from a sample of network similarities. Note that using all data can double the memory footprint of the function and the function may fail.
`sampleForCalibrationFactor`	Determines the number of samples for calibration: the number is `1/calibrationQuantile * sampleForCalibrationFactor`. Should be set well above 1 to ensure accuracy of the sampled quantile.
`consensusQuantile`	Quantile at which consensus is to be defined. See details.
`useMean`	Logical: should the consensus be calculated using (weighted) mean rather than a quantile?
`setWeights`	Optional specification of weights when `useMean` is `TRUE`.
`analysisName`	Optional character string naming the consensus analysis. Useful for identifying partial consensus calculation in hierarchical consensus analysis.