Add TF-peak connections to a GRN object

After the execution of this function, QC plots can be plotted with the function plotDiagnosticPlots_TFPeaks unless this has already been done by default due to plotDiagnosticPlots = TRUE

addConnections_TF_peak(
  GRN,
  plotDiagnosticPlots = TRUE,
  plotDetails = FALSE,
  outputFolder = NULL,
  corMethod = "pearson",
  connectionTypes = c("expression"),
  removeNegativeCorrelation = c(FALSE),
  maxFDRToStore = 0.3,
  addForBackground = TRUE,
  useGCCorrection = FALSE,
  percBackground_size = 75,
  percBackground_resample = TRUE,
  forceRerun = FALSE
)

Arguments

GRN

Object of class GRN

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).

plotDetails

TRUE or FALSE. Default FALSE. Print additional plots that may help for debugging and QC purposes? Note that these plots are currently less documented or not at all.

outputFolder

Character or NULL. Default NULL. If set to NULL, the default output folder as specified when initiating the object in initializeGRN will be used. Otherwise, all output from this function will be put into the specified folder. If a folder is provided, while we recommend specifying an absolute path, a relative one also works.

corMethod

Character. One of pearson, spearman or bicor. Default pearson. Method for calculating the correlation coefficient. For pearson and spearman , see cor for details. bicor denotes the *biweight midcorrelation*, a correlation measure based on medians as calculated by WGCNA::bicorAndPvalue. Both spearman and bicor are considered more robust measures that are less prone to be affected by outliers.

connectionTypes

Character vector. Default expression. Vector of connection types to include for the TF-peak connections. If an additional connection type is specified here, it has to be available already within the object (EXPERIMENTAL). See the function addData_TFActivity for details.

removeNegativeCorrelation

Vector of TRUE or FALSE. Default FALSE. EXPERIMENTAL. Must be a logical vector of the same length as the parameter connectionType. Should negatively correlated TF-peak connections be removed for the specific connection type? For connection type expression, the default is FALSE, while for any TF Activity related connection type, we recommend setting this to TRUE.

maxFDRToStore

Numeric[0,1]. Default 0.3. Maximum TF-peak FDR value to permanently store a particular TF-peak connection in the object? This parameter has a large influence on the overall memory size of the object, and we recommend not storing connections with a high FDR due to their sheer number.

addForBackground

TRUE or FALSE. Default TRUE. Add connections also for background data. Leave at TRUE unless you know what you are doing.

useGCCorrection

TRUE or FALSE. Default FALSE. EXPERIMENTAL. Should a GC-matched background be used when calculating FDRs? For more details, see the Package Details vignette.

percBackground_size

Numeric[0,100]. Default 75. EXPERIMENTAL. Percentage of the background to use as basis for sampling. If set to 0, an automatic iterative procedure will identify the maximum percentage so that all relevant GC bins with a rel. frequency above 5% from the foreground can be matched. For more details, see the Package Details vignette. Only relevant if useGCCorrection is set to TRUE, ignored otherwise.

percBackground_resample

TRUE or FALSE. Default TRUE. EXPERIMENTAL. Should resampling be enabled for those GC bins for which not enough background peaks are available?. For more details, see the Package Details vignette. Only relevant if useGCCorrection is set to TRUE, ignored otherwise.

forceRerun

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

Value

An updated GRN object, with additional information added from this function.

Examples

# See the Workflow vignette on the GRaNIE website for examples
GRN = loadExampleObject()
#> Downloading GRaNIE example object from https://git.embl.de/grp-zaugg/GRaNIE/-/raw/master/data/GRN.rds
#> INFO [2023-08-16 17:26:47] Storing GRN@data$RNA$counts matrix as sparse matrix because fraction of 0s is > 0.1 (0.44)
#> Finished successfully. You may explore the example object. Start by typing the object name to the console to see a summaty. Happy GRaNIE'ing!
GRN = addConnections_TF_peak(GRN, plotDiagnosticPlots = FALSE, forceRerun = FALSE)
#> INFO [2023-08-16 17:26:47] Data already exists in object or the specified file already exists. Set forceRerun = TRUE to regenerate and overwrite.
#> INFO [2023-08-16 17:26:47] Finished successfully. Execution time: 0 secs