Data_Prep {GmicR} | R Documentation

## Discretizes biological assay data in preparation for bayensian network learning

### Description

Discretizes biological assay data in preparation for bayensian network learning

### Usage

    Data_Prep(
      Auto_WGCNA_OUTPUT = NULL,
      Remove_ME0 = FALSE,
      Numeric_Pheno_scores = NULL,
      xCell_Signatures = NULL,
      ibreaks = 60
    )

### Arguments

`Auto_WGCNA_OUTPUT` | R object generated from Auto_WGCNA function.
`Remove_ME0` | a logical value. If FALSE (default), ME0 is not removed. If TRUE the eigengene for module 0 is removed prior to analysis.
`Numeric_Pheno_scores` | a data.frame with rows indicating sample ID and columns representing additional phenotype data to be included in BN learning. If NULL (default) no data will be included. If provided, the data.frame will be merged with MEs and discretized into three levels.
`xCell_Signatures` | the name of the text file generated by xCell that contains the cell signature scores. If NULL (default) the only module eigenegnes will be processed. If not NULL and if Auto_WGCNA_OUTPUT is NULL, cell signature scores will be discretized.
`ibreaks` | an integer that indicates the number of ibreaks used for discretization. The default value is 60.

### Value

a list containing a data.frame with module eigenegnes merged with Xcell signature scores and discretized into three levels: L, M, H. If Auto_WGCNA_OUTPUT is NULL, both scaled and discretized cell signatures will be return.

### Note

Please verify that the sample name formatting is consistent between both datasets. Rownames in the module eigengenes data.frame and the column names of xCell signatures scores text file are matched for merging. Only samples that are present in both will be processed!

### Examples

    file_dir<-system.file("extdata", "IRIS_xCell_sig.txt",
    package = "GmicR", mustWork = TRUE)
    Disc_Xcell_sig<-Data_Prep(xCell_Signatures=file_dir, ibreaks = 10)
    Disc_Xcell_sig$disc_data

[Package GmicR version 1.4.0 Index]