pruneAndMergeConsensusModules: Iterative pruning and merging of (hierarchical) consensus...

Description Usage Arguments Value Author(s) See Also

View source: R/hierarchicalConsensusModules.R

Description

This function prunes genes with low consensus eigengene-based intramodular connectivity (kME) from modules and merges modules whose consensus similarity is high. The process is repeated until the modules become stable.

Usage

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pruneAndMergeConsensusModules(
  multiExpr,
  multiWeights = NULL,
  multiExpr.imputed = NULL,
  labels,
  unassignedLabel = if (is.numeric(labels)) 0 else "grey",
  networkOptions,
  consensusTree,

  # Pruning options
  minModuleSize,
  minCoreKMESize = minModuleSize/3,
  minCoreKME = 0.5, 
  minKMEtoStay = 0.2,

  # Module eigengene calculation and merging options
  impute = TRUE,
  trapErrors = FALSE,
  calibrateMergingSimilarities = FALSE,
  mergeCutHeight = 0.15,

  # Behavior
  iterate = TRUE,
  collectGarbage = FALSE,
  getDetails = TRUE,
  verbose = 1, indent=0)

Arguments

multiExpr

Expression data in the multi-set format (see checkSets). A vector of lists, one per set. Each set must contain a component data that contains the expression data, with rows corresponding to samples and columns to genes or probes.

multiWeights

optional observation weights in the same format (and dimensions) as multiExpr. These weights are used for correlation calculations with data in multiExpr.

multiExpr.imputed

If multiExpr contain missing data, this argument can be used to supply the expression data with missing data imputed. If not given, the impute.knn function will be used to impute the missing data.

labels

A vector (numeric, character or a factor) giving module labels for each variable (gene) in multiExpr.

unassignedLabel

The label (value in labels) that represents unassigned genes. Module of this label will not enter the module eigengene clustering and will not be merged with other modules.

networkOptions

A single list of class NetworkOptions giving options for network calculation for all of the networks, or a multiData structure containing one such list for each input data set.

consensusTree

A list of class ConsensusTree specifying the consensus calculation.

minModuleSize

Minimum number of genes in a module. Modules that have fewer genes (after trimming) will be removed (i.e., their genes will be given the unassigned label).

minCoreKME

a number between 0 and 1. If a detected module does not have at least minModuleKMESize genes with consensus eigengene connectivity at least minCoreKME, the module is disbanded (its genes are unlabeled).

minCoreKMESize

see minCoreKME above.

minKMEtoStay

genes whose consensus eigengene connectivity to their module eigengene is lower than minKMEtoStay are removed from the module.

impute

logical: should imputation be used for module eigengene calculation? See moduleEigengenes for more details.

trapErrors

logical: should errors in calculations be trapped?

calibrateMergingSimilarities

Logical: should module eigengene similarities be calibrated before calculating the consensus? Although calibration is in principle desirable, the calibration methods currently available assume large data and do not work very well on eigengene similarities.

mergeCutHeight

Dendrogram cut height for module merging.

iterate

Logical: should the pruning and merging process be iterated until no changes occur? If FALSE, only one iteration will be carried out.

collectGarbage

Logical: should garbage be collected after some of the memory-intensive steps?

getDetails

Logical: should certain intermediate results be returned? These include labels and module merging information at each iteration (see return value).

verbose

integer level of verbosity. 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.

Value

If input getDetails is FALSE, a vector the resulting module labels. If getDetails is TRUE, a list with these components:

labels

The resulting module labels

details

A list. The first component, named originalLabels, contains a copy of the input labels. The following components are named Iteration.1, Iteration.2 etc and contain, for each iteration, components prunedLabels (the result of pruning in that iteration) and mergeInfo (result of the call to hierarchicalMergeCloseModules in that iteration).

Author(s)

Peter Langfelder

See Also

The underlying functions pruneConsensusModules and hierarchicalMergeCloseModules.


WGCNA documentation built on March 1, 2021, 1:05 a.m.