Auto_WGCNA {GmicR} | R Documentation

## Carries out WGCNA with default settings or custom settings

### Description

Carries out WGCNA with default settings or custom settings

### Usage

    Auto_WGCNA(
      datExpr,
      colname_correct = TRUE,
      minModuleSize = 10,
      deepSplit = 4,
      networkType = "signed hybrid",
      TOMType = "unsigned",
      corFnc = "bicor",
      mergeCutHeight = 0.25,
      sft_RsquaredCut = 0.85,
      removeFirst = FALSE,
      reassignThreshold = 1e-06,
      maxBlockSize = 25000,
      nThreads = NULL
    )

### Arguments

`datExpr` | Expression data. A matrix (preferred) or data frame in which columns are genes and rows ar samples. NAs are allowed, but not too many. See `checkMissingData` below and details.
`colname_correct` | a logical value. If TRUE (default), "." in gene names will be replaced with "-". This corrects a name change that is induced by R when creating a data.frame. If FALSE, no changes will be made.
`minModuleSize` | minimum module size for module detection. See `cutreeDynamic` for more details.
`deepSplit` | integer value between 0 and 4. Provides a simplified control over how sensitive module detection should be to module splitting, with 0 least and 4 most sensitive. See `cutreeDynamic` for more details.
`networkType` | network type. Allowed values are (unique abbreviations of) `"unsigned"`, `"signed"`, `"signed hybrid"`. See `adjacency`.
`TOMType` | one of `"none"`, `"unsigned"`, `"signed"`. If `"none"`, adjacency will be used for clustering. If `"unsigned"`, the standard TOM will be used (more generally, TOM function will receive the adjacency as input). If `"signed"`, TOM will keep track of the sign of correlations between neighbors.
`corFnc` | the correlation function to be used in adjacency calculation.
`mergeCutHeight` | dendrogram cut height for module merging.
`sft_RsquaredCut` | desired minimum scale free topology fitting index R^2. Default is 0.80.
`removeFirst` | should the first bin be removed from the connectivity histogram?
`reassignThreshold` | p-value ratio threshold for reassigning genes between modules. See Details.
`maxBlockSize` | integer giving maximum block size for module detection. Ignored if `blocks` above is non-NULL. Otherwise, if the number of genes in `datExpr` exceeds `maxBlockSize`, genes will be pre-clustered into blocks whose size should not exceed `maxBlockSize`.
`nThreads` | non-negative integer specifying the number of parallel threads to be used by certain parts of correlation calculations. This option only has an effect on systems on which a POSIX thread library is available (which currently includes Linux and Mac OSX, but excludes Windows). If zero, the number of online processors will be used if it can be determined dynamically, otherwise correlation calculations will use 2 threads.

### Value

Returns a lists containing network input parameters used for WGCNA, WGCNA module information, and quality control plots.

### Note

This is a wrapper for WGCNA.

### See Also

`blockwiseModules`

`adjacency`

### Examples

    sample_dat_dir<-system.file("extdata", "sample_dat.Rdata",
    package = "GmicR", mustWork = TRUE)
    load(sample_dat_dir)
    GMIC_Builder<-Auto_WGCNA(sample_dat, mergeCutHeight = 0.35,
    minModuleSize = 10)

[Package GmicR version 1.6.0 Index]