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,
      reassignThreshold = 1e-06,
      maxBlockSize = 25000
    )

### 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` | character string specifying the function to be used to calculate co-expression similarity for correlation networks. Defaults to Pearson correlation. Any function returning values between -1 and 1 can be used.
`mergeCutHeight` | dendrogram cut height for module merging.
`sft_RsquaredCut` | desired minimum scale free topology fitting index R^2. Default is 0.80.
`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`.

### 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 1.0.6 Index]