AR_classification_wrapper: Run the activator-repressor classification for the TFs for a...

AR_classification_wrapperR Documentation

Run the activator-repressor classification for the TFs for a GRN object

Description

Run the activator-repressor classification for the TFs for a GRN object

Usage

AR_classification_wrapper(
  GRN,
  significanceThreshold_Wilcoxon = 0.05,
  plot_minNoTFBS_heatmap = 100,
  deleteIntermediateData = TRUE,
  plotDiagnosticPlots = TRUE,
  outputFolder = NULL,
  corMethod = "pearson",
  forceRerun = FALSE
)

Arguments

GRN

Object of class GRN

significanceThreshold_Wilcoxon

Numeric between 0 and 1. Default 0.05. Significance threshold for Wilcoxon test that is run in the end for the final classification. See the Vignette and *diffTF* paper for details.

plot_minNoTFBS_heatmap

Integer. Default 100. Minimum number of TFBS for a TF to be included in the heatmap that is part of the output of this function.

deleteIntermediateData

TRUE or FALSE. Default TRUE. Should intermediate data be deleted before returning the object after a successful run? Due to the size of the produced intermediate data, we recommend setting this to TRUE, but if memory or object size are not an issue, the information can also be kept.

plotDiagnosticPlots

TRUE or FALSE. Default TRUE. Run and plot various diagnostic plots? If set to TRUE, PDF files will be produced and saved in the output directory (in a subfolder called plots).

outputFolder

Character or NULL. Default NULL. If set to NULL, the default output folder as specified when initiating the object in link{initializeGRN} will be used. Otherwise, all output from this function will be put into the specified folder. We recommend specifying an absolute path.

corMethod

Character. pearson or spearman. Default pearson. Method for calculating the correlation coefficient. See cor for details.

forceRerun

TRUE or FALSE. Default FALSE. Force execution, even if the GRN object already contains the result. Overwrites the old results.

Value

The same GRN object, with added data from this function.

Examples

# See the Workflow vignette on the GRaNIE website for examples
# GRN = loadExampleObject()
# GRN = AR_classification_wrapper(GRN, outputFolder = ".", forceRerun = FALSE)

chrarnold/GRaNIE documentation built on April 28, 2022, 2:18 a.m.