wgcna_db: wgcna function wrapper
In ddeweerd/MODifieRDB: MODifieRDB

wgcna function wrapper

wgcna_db(
  input_name,
  group_of_interest,
  minModuleSize = 30,
  deepSplit = 2,
  to_db = TRUE,
  folder = NULL,
  pamRespectsDendro = FALSE,
  mergeCutHeight = 0.1,
  numericLabels = TRUE,
  pval_cutoff = 0.05,
  corType = "bicor",
  maxBlockSize = 10000,
  TOMType = "signed",
  saveTOMs = TRUE,
  maxPOutliers = 0.1,
  module_name,
  con
)

`input_name`	Name of the input object in the database
`group_of_interest`	Numerical value denoting which group contains the condition of interest (1 or 2)
`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.
`to_db`	Save result in database, default is TRUE
`folder`	If not saved in database, folder where to save the module as .rds
`pamRespectsDendro`	Logical, only used when `pamStage` is `TRUE`. If `TRUE`, the PAM stage will respect the dendrogram in the sense an object can be PAM-assigned only to clusters that lie below it on the branch that the object is merged into. See `cutreeDynamic` for more details.
`mergeCutHeight`	dendrogram cut height for module merging.
`numericLabels`	logical: should the returned modules be labeled by colors (`FALSE`), or by numbers (`TRUE`)?
`pval_cutoff`	The p-value cutoff to be used for significant co-expression modules (colors)
`corType`	character string specifying the correlation to be used. Allowed values are (unique abbreviations of) `"pearson"` and `"bicor"`, corresponding to Pearson and bidweight midcorrelation, respectively. Missing values are handled using the `pairwise.complete.obs` option.
`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`.
`TOMType`	one of `"none"`, `"unsigned"`, `"signed"`, `"signed Nowick"`, `"unsigned 2"`, `"signed 2"` and `"signed Nowick 2"`. If `"none"`, adjacency will be used for clustering. See `TOMsimilarityFromExpr` for details.
`saveTOMs`	logical: should the consensus topological overlap matrices for each block be saved and returned?
`maxPOutliers`	only used for `corType=="bicor"`. Specifies the maximum percentile of data that can be considered outliers on either side of the median separately. For each side of the median, if higher percentile than `maxPOutliers` is considered an outlier by the weight function based on `9*mad(x)`, the width of the weight function is increased such that the percentile of outliers on that side of the median equals `maxPOutliers`. Using `maxPOutliers=1` will effectively disable all weight function broadening; using `maxPOutliers=0` will give results that are quite similar (but not equal to) Pearson correlation.
`module_name`	Unique name for the module object when stored in database
`con`	Database connection obtained with `connect_to_db` function