Browse code

Various small edits

Christian Arnold authored on 19/03/2022 18:55:41
Showing18 changed files

... ...
@@ -1506,8 +1506,8 @@ importTFData <- function(GRN, data, name, idColumn = "ENSEMBL", nameColumn = "TF
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 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.  
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 #' @examples 
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 #' # See the Workflow vignette on the GRaNIE website for examples
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-#' GRN = loadExampleObject()
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-#' GRN = AR_classification_wrapper(GRN, outputFolder = ".", forceRerun = FALSE)
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+#' # GRN = loadExampleObject()
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+#' # GRN = AR_classification_wrapper(GRN, outputFolder = ".", forceRerun = FALSE)
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 #' @export
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 AR_classification_wrapper<- function (GRN, significanceThreshold_Wilcoxon = 0.05, 
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                                       plot_minNoTFBS_heatmap = 100, deleteIntermediateData = TRUE,
... ...
@@ -2276,7 +2276,8 @@ addConnections_TF_peak <- function (GRN, plotDiagnosticPlots = TRUE, plotDetails
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 #' @examples 
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 #' # See the Workflow vignette on the GRaNIE website for examples
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 #' GRN = loadExampleObject()
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-#' GRN = addConnections_peak_gene(GRN, promoterRange = 10000, outputFolder = ".")
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+#' types =  list(c("protein_coding"))
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+#' GRN = addConnections_peak_gene(GRN, promoterRange=10000, outputFolder=".", plotGeneTypes=types)
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 addConnections_peak_gene <- function(GRN, overlapTypeGene = "TSS", corMethod = "pearson",
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                                      promoterRange = 250000, TADs = NULL,
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                                      nCores = 4, 
... ...
@@ -3465,23 +3466,23 @@ add_TF_gene_correlation <- function(GRN, corMethod = "pearson", addRobustRegress
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         res.df = suppressMessages(tibble::as_tibble(res.m) %>%
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                                     dplyr::mutate(TF.ENSEMBL   = getCounts(GRN, type = "rna", norm = TRUE, permuted = as.logical(permutationCur))$ENSEMBL[map_TF],
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                                                   gene.ENSEMBL = getCounts(GRN, type = "rna", norm = TRUE, permuted = as.logical(permutationCur))$ENSEMBL[map_gene]) %>%
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-                                    dplyr::filter(!is.na(gene.ENSEMBL), !is.na(TF.ENSEMBL)) %>%  # For some peak-gene combinations, no RNA-Seq data was available, these NAs are filtered
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+                                    dplyr::filter(!is.na(.data$gene.ENSEMBL), !is.na(.data$TF.ENSEMBL)) %>%  # For some peak-gene combinations, no RNA-Seq data was available, these NAs are filtered
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                                     dplyr::left_join(GRN@data$TFs$translationTable, by = c("TF.ENSEMBL")) %>%
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                                     dplyr::select(tidyselect::all_of(selectColumns))) %>%
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-          dplyr::mutate(gene.ENSEMBL = as.factor(gene.ENSEMBL), 
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-                        TF.ENSEMBL   = as.factor(TF.ENSEMBL),
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-                        TF.name           = as.factor(TF.name)) %>%
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-          dplyr::rename(TF_gene.r     = r, 
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-                        TF_gene.p_raw = p.raw) %>%
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+          dplyr::mutate(gene.ENSEMBL = as.factor(.data$gene.ENSEMBL), 
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+                        TF.ENSEMBL   = as.factor(.data$TF.ENSEMBL),
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+                        TF.name           = as.factor(.data$TF.name)) %>%
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+          dplyr::rename(TF_gene.r     = .data$r, 
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+                        TF_gene.p_raw = .data$p.raw) %>%
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           dplyr::select(TF.name, TF.ENSEMBL, gene.ENSEMBL, tidyselect::everything())
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         if (addRobustRegression) {
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           res.df = dplyr::rename(res.df, 
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-                                 TF_gene.p_raw.robust = p_raw.robust, 
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-                                 TF_gene.r_robust = r_robust,
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-                                 TF_gene.bias_M_p.raw = bias_M_p.raw,
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-                                 TF_gene.bias_LS_p.raw = bias_LS_p.raw)
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+                                 TF_gene.p_raw.robust = .data$p_raw.robust, 
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+                                 TF_gene.r_robust = .data$r_robust,
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+                                 TF_gene.bias_M_p.raw = .data$bias_M_p.raw,
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+                                 TF_gene.bias_LS_p.raw = .data$bias_LS_p.raw)
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         }
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       } else {
... ...
@@ -3643,7 +3644,7 @@ addSNPOverlap <- function(grn, SNPData, col_chr = "chr", col_pos = "pos", col_pe
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 #' @examples 
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 #' # See the Workflow vignette on the GRaNIE website for examples
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 #' GRN = loadExampleObject()
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-#' GRN = generateStatsSummary(GRN, forceRerun = FALSE)
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+#' GRN = generateStatsSummary(GRN, TF_peak.fdr = c(0.01, 0.1), peak_gene.fdr = c(0.01, 0.1))
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 #' 
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 generateStatsSummary <- function(GRN, 
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                                  TF_peak.fdr = c(0.001, 0.01, 0.05, 0.1, 0.2),
... ...
@@ -3931,9 +3932,9 @@ loadExampleObject <- function(forceDownload = FALSE, fileURL = "https://www.embl
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   bfc <- .get_cache()
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-  rid <- BiocFileCache::bfcquery(bfc, "geneFileV2", "rname")$rid
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+  rid <- BiocFileCache::bfcquery(bfc, "GRaNIE_object_example")$rid
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   if (!length(rid)) {
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-    rid <- names(BiocFileCache::bfcadd(bfc, "geneFileV2", fileURL))
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+    rid <- names(BiocFileCache::bfcadd(bfc, "GRaNIE_object_example", fileURL))
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   }
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   if (isFALSE(BiocFileCache::bfcneedsupdate(bfc, rid)) | forceDownload) {
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     messageStr = paste0("Downloading GRaNIE example object from ", fileURL)
... ...
@@ -4237,7 +4238,7 @@ getGRNConnections <- function(GRN, type = "all.filtered",  permuted = FALSE, inc
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 #' @examples 
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 #' # See the Workflow vignette on the GRaNIE website for examples
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 #' GRN = loadExampleObject()
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-#' getParameters(GRN, type = "parameter", name = "all")
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+#' params.l = getParameters(GRN, type = "parameter", name = "all")
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 getParameters <- function (GRN, type = "parameter", name = "all") {
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   checkmate::assertClass(GRN, "GRN")
... ...
@@ -4362,12 +4363,12 @@ getBasic_metadata_visualization <- function(GRN, forceRerun = FALSE) {
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 #' 
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 #' @export
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 #' @template GRN
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-#' @param outputDirectory 
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+#' @param outputDirectory Character. Default \code{.}. New output directory for all output files unless overwritten via the parameter \code{outputFolder}.
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 #' @return The same \code{\linkS4class{GRN}} object, with the output directory being adjusted accordingly
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 #' @examples 
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-#' # GRN = loadExampleObject()
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-#' # GRN = changeOutputDirectory(GRN, ".")
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-changeOutputDirectory <- function(GRN, outputDirectory) {
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+#' GRN = loadExampleObject()
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+#' GRN = changeOutputDirectory(GRN, outputDirectory = ".")
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+changeOutputDirectory <- function(GRN, outputDirectory = ".") {
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   GRN@config$directories$outputRoot   =  outputDirectory
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   GRN@config$directories$output_plots = paste0(outputDirectory, "/plots/")
... ...
@@ -200,8 +200,8 @@ build_eGRN_graph <- function(GRN, model_TF_gene_nodes_separately = FALSE,
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 #' @export
201 201
 #' @examples 
202 202
 #' # See the Workflow vignette on the GRaNIE website for examples
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-#' GRN = loadExampleObject()
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-#' GRN = performAllNetworkAnalyses(GRN, outputFolder = ".", forceRerun = FALSE)
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+#' # GRN = loadExampleObject()
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+#' # GRN = performAllNetworkAnalyses(GRN, outputFolder = ".", forceRerun = FALSE)
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 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.
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 performAllNetworkAnalyses <- function(GRN, ontology = c("GO_BP", "GO_MF"), 
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                                       algorithm = "weight01", statistic = "fisher",
... ...
@@ -17,7 +17,7 @@
17 17
 #' @examples 
18 18
 #' # See the Workflow vignette on the GRaNIE website for examples
19 19
 #' GRN = loadExampleObject()
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-#' GRN = plotPCA_all(GRN, topn = 500, outputFolder = ".", forceRerun = FALSE)
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+#' GRN = plotPCA_all(GRN, topn = 500, outputFolder = ".", type = "rna", plotAsPDF=FALSE)
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 #' @export
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 plotPCA_all <- function(GRN, outputFolder = NULL, basenameOutput = NULL, 
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                         type = c("rna", "peaks"), topn = c(500,1000,5000), 
... ...
@@ -443,22 +443,28 @@ plotPCA_all <- function(GRN, outputFolder = NULL, basenameOutput = NULL,
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444 444
 
445 445
 #' Plot diagnostic plots for TF-peak connections for a \code{\linkS4class{GRN}} object
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+#' 
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+#' Due to the number of plots that this functions produces, we currently provide only the option to plot as PDF. This may change in the future.
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 #'
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 #' @template GRN 
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 #' @template outputFolder
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 #' @template basenameOutput
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 #' @template plotDetails
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+#' @param plotPermuted \code{TRUE} or \code{FALSE}. Default  \code{TRUE}. Also produce the diagnostic plots for permuted data?
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+#' @param nTFMax \code{NULL} or Integer. Default \code{NULL}. Maximum number of TFs to process. Can be used for testing purposes by setting this to a small number i(.e., 10)
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 #' @template forceRerun
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 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.
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 #' @examples 
454 458
 #' # See the Workflow vignette on the GRaNIE website for examples
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 #' GRN = loadExampleObject()
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-#' GRN = plotDiagnosticPlots_TFPeaks(GRN, outputFolder = ".", forceRerun = FALSE)
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+#' GRN = plotDiagnosticPlots_TFPeaks(GRN, outputFolder = ".", plotPermuted = FALSE, nTFMax = 2)
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 #' @export
458 462
 plotDiagnosticPlots_TFPeaks <- function(GRN, 
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                                         outputFolder = NULL, 
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                                         basenameOutput = NULL, 
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                                         plotDetails = FALSE,
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+                                        plotPermuted = TRUE,
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+                                        nTFMax = NULL,
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                                         forceRerun = FALSE) {
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   GRN = .addFunctionLogToObject(GRN)
... ...
@@ -467,6 +473,8 @@ plotDiagnosticPlots_TFPeaks <- function(GRN,
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   checkmate::assert(checkmate::checkNull(outputFolder), checkmate::checkCharacter(outputFolder, min.chars = 1))
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   checkmate::assert(checkmate::checkNull(basenameOutput), checkmate::checkCharacter(basenameOutput, len = 1, min.chars = 1, any.missing = FALSE))
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   checkmate::assertFlag(plotDetails)
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+  checkmate::assertFlag(plotPermuted)
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+  checkmate::assert(checkmate::checkNull(nTFMax), checkmate::checkIntegerish(nTFMax))
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   checkmate::assertFlag(forceRerun)
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   useGCCorrection = GRN@config$parameters$useGCCorrection
... ...
@@ -476,6 +484,10 @@ plotDiagnosticPlots_TFPeaks <- function(GRN,
476 484
   
477 485
   for (permutationCur in 0:.getMaxPermutation(GRN)) {
478 486
     
487
+    if (!plotPermuted & permutationCur != 0) {
488
+      next
489
+    }
490
+    
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     suffixFile = .getPermutationSuffixStr(permutationCur)
480 492
     
481 493
     fileCur = paste0(outputFolder, 
... ...
@@ -485,7 +497,9 @@ plotDiagnosticPlots_TFPeaks <- function(GRN,
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     if (!file.exists(fileCur) | forceRerun) {
486 498
       
487 499
       heightCur = 8* length(GRN@config$TF_peak_connectionTypes)
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-      .plot_TF_peak_fdr(GRN, perm = permutationCur, useGCCorrection = useGCCorrection, plotDetails = plotDetails, fileCur, width = 7, height = heightCur) 
500
+      .plot_TF_peak_fdr(GRN, perm = permutationCur, useGCCorrection = useGCCorrection, 
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+                        plotDetails = plotDetails, fileCur, width = 7, height = heightCur,
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+                        nPagesMax = nTFMax) 
489 503
     }
490 504
     
491 505
     fileCur = paste0(outputFolder, .getOutputFileName("plot_TFPeak_fdr_GC"), suffixFile)
... ...
@@ -623,20 +637,24 @@ plotDiagnosticPlots_TFPeaks <- function(GRN,
623 637
     index = 1
624 638
   } 
625 639
   
640
+  # Dont take all TF, some might be missing.
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   connections_TF_peak = GRN@connections$TF_peaks[[as.character(perm)]]$connectionStats
642
+  allTF = unique(connections_TF_peak$TF.name)
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+  nTF = ifelse(is.null(nPagesMax), length(allTF), nPagesMax)
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+  futile.logger::flog.info(paste0(" Including a total of ", nTF,  " TF. Preparing plots..."))
627 645
   
628
-  # TODO: Check difference between TFActivity TFs and expression TFs
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630
-  # Dont take all TF, some might be missing.
631
-  allTF = unique(connections_TF_peak$TF.name)
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-  futile.logger::flog.info(paste0(" Including a total of ", length(allTF),  " TF. Preparing plots..."))
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+  # TODO: Check difference between TFActivity TFs and expression TFs
633 648
   
634
-  pb <- progress::progress_bar$new(total = length(allTF))
649
+
650
+  pb <- progress::progress_bar$new(total = nTF)
635 651
   
636 652
   levels_pos<-unique(as.character(cut(GRN@config$parameters$internal$stepsFDR, breaks = GRN@config$parameters$internal$stepsFDR, right = FALSE, include.lowest = TRUE )))
637 653
   levels_neg<-unique(as.character(cut(GRN@config$parameters$internal$stepsFDR, breaks = rev(GRN@config$parameters$internal$stepsFDR), right = TRUE,  include.lowest = TRUE )))
638 654
   
639
-  for (i in seq_len(length(allTF))) {
655
+
656
+  
657
+  for (i in seq_len(nTF)) {
640 658
     pb$tick()
641 659
     TFCur = allTF[i]
642 660
     
... ...
@@ -758,11 +776,7 @@ plotDiagnosticPlots_TFPeaks <- function(GRN,
758 776
   
759 777
   if (!is.null(file)) {
760 778
     futile.logger::flog.info(paste0(" Finished generating plots, start plotting to file ",file, ". This may take a few minutes."))
761
-    if (!is.null(nPagesMax)) {
762
-      .printMultipleGraphsPerPage(plots.l[c(seq_len(nPagesMax))], nCol = 1, nRow = 2, pdfFile = file, height = height, width = width)
763
-    } else {
764
-      .printMultipleGraphsPerPage(plots.l, nCol = 1, nRow = 2, pdfFile = file, height = height, width = width)
765
-    }
779
+    .printMultipleGraphsPerPage(plots.l, nCol = 1, nRow = 2, pdfFile = file, height = height, width = width)
766 780
     
767 781
   }
768 782
   
... ...
@@ -794,7 +808,8 @@ plotDiagnosticPlots_TFPeaks <- function(GRN,
794 808
 #' @examples 
795 809
 #' # See the Workflow vignette on the GRaNIE website for examples
796 810
 #' # GRN = loadExampleObject()
797
-#' # GRN = plotDiagnosticPlots_peakGene(GRN, outputFolder = ".", forceRerun = FALSE)
811
+#' # types = list(c("protein_coding"))
812
+#' # GRN = plotDiagnosticPlots_peakGene(GRN, outputFolder=".", gene.types=types, plotAsPDF=FALSE)
798 813
 #' @export
799 814
 # TODO: implement forceRerun correctly
800 815
 plotDiagnosticPlots_peakGene <- function(GRN, 
... ...
@@ -1318,7 +1333,7 @@ plotDiagnosticPlots_peakGene <- function(GRN,
1318 1333
           #theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 8), strip.background = element_blank(), strip.placement = "outside", axis.title.y = element_blank()) +
1319 1334
           # theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 8) , axis.title.y = element_blank()) +
1320 1335
           theme_main +
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-          facet_wrap(~ factor(class), nrow = 2, scales = "free_y", strip.position = "left", , labeller = labeller(class=freq_class)) 
1336
+          facet_wrap(~ factor(class), nrow = 2, scales = "free_y", strip.position = "left", labeller = labeller(class=freq_class)) 
1322 1337
         
1323 1338
         
1324 1339
         plots_all = ( ((gA3 | gB3 ) + 
... ...
@@ -1584,7 +1599,7 @@ plotDiagnosticPlots_peakGene <- function(GRN,
1584 1599
 #' @examples 
1585 1600
 #' # See the Workflow vignette on the GRaNIE website for examples
1586 1601
 #' GRN = loadExampleObject()
1587
-#' GRN = plot_stats_connectionSummary(GRN, outputFolder = ".", forceRerun = FALSE)
1602
+#' GRN = plot_stats_connectionSummary(GRN, outputFolder = ".", forceRerun = FALSE, plotAsPDF=FALSE)
1588 1603
 #' @export
1589 1604
 #' @importFrom circlize colorRamp2
1590 1605
 plot_stats_connectionSummary <- function(GRN, type = "heatmap", 
... ...
@@ -1613,6 +1628,7 @@ plot_stats_connectionSummary <- function(GRN, type = "heatmap",
1613 1628
     }
1614 1629
     
1615 1630
     .plot_stats_connectionSummaryHeatmap(GRN, file = file, pdf_width = pdf_width, pdf_height = pdf_height, forceRerun = forceRerun) 
1631
+  
1616 1632
   } else if (type ==  "boxplot") {
1617 1633
     
1618 1634
     if (plotAsPDF) {
... ...
@@ -1645,7 +1661,7 @@ plot_stats_connectionSummary <- function(GRN, type = "heatmap",
1645 1661
   
1646 1662
   futile.logger::flog.info(paste0("Plotting connection summary", dplyr::if_else(is.null(file), "", paste0(" to file ", file))))
1647 1663
   
1648
-  if ((!is.null(file) & !file.exists(file))| forceRerun) {
1664
+  if ((!is.null(file) && !file.exists(file))| forceRerun) {
1649 1665
     
1650 1666
     if (nrow(GRN@stats$connections) == 0) {
1651 1667
       message = paste0("Statistics summary missing from object, please run the function generateStatsSummary first")
... ...
@@ -1776,7 +1792,7 @@ plot_stats_connectionSummary <- function(GRN, type = "heatmap",
1776 1792
   
1777 1793
   start = Sys.time()
1778 1794
   
1779
-  if ((!is.null(file) & !file.exists(file))| forceRerun) {
1795
+  if ((!is.null(file) && !file.exists(file))| forceRerun) {
1780 1796
     
1781 1797
     
1782 1798
     futile.logger::flog.info(paste0("Plotting diagnostic plots for network connections", dplyr::if_else(is.null(file), "", paste0(" to file ", file))))
... ...
@@ -1915,7 +1931,7 @@ plot_stats_connectionSummary <- function(GRN, type = "heatmap",
1915 1931
 #' @examples 
1916 1932
 #' # See the Workflow vignette on the GRaNIE website for examples
1917 1933
 #' GRN = loadExampleObject()
1918
-#' GRN = plotGeneralGraphStats(GRN, outputFolder = ".", forceRerun = FALSE)
1934
+#' GRN = plotGeneralGraphStats(GRN, outputFolder = ".", plotAsPDF=FALSE)
1919 1935
 #' @export
1920 1936
 plotGeneralGraphStats <- function(GRN, outputFolder = NULL, basenameOutput = NULL, 
1921 1937
                                   plotAsPDF = TRUE, pdf_width = 12, pdf_height = 12, 
... ...
@@ -2081,7 +2097,7 @@ plotGeneralGraphStats <- function(GRN, outputFolder = NULL, basenameOutput = NUL
2081 2097
 #' @examples 
2082 2098
 #' # See the Workflow vignette on the GRaNIE website for examples
2083 2099
 #' GRN = loadExampleObject()
2084
-#' GRN = plotGeneralEnrichment(GRN, outputFolder = ".", forceRerun = FALSE)
2100
+#' GRN = plotGeneralEnrichment(GRN, outputFolder = ".", plotAsPDF=FALSE)
2085 2101
 #' @export
2086 2102
 plotGeneralEnrichment <- function(GRN, outputFolder = NULL, basenameOutput = NULL, 
2087 2103
                                   ontology = NULL, topn_pvalue = 30, p = 0.05, 
... ...
@@ -2260,7 +2276,7 @@ plotGeneralEnrichment <- function(GRN, outputFolder = NULL, basenameOutput = NUL
2260 2276
 #' @examples 
2261 2277
 #' # See the Workflow vignette on the GRaNIE website for examples
2262 2278
 #' GRN = loadExampleObject()
2263
-#' GRN = plotCommunitiesStats(GRN, outputFolder = ".", forceRerun = FALSE)
2279
+#' GRN = plotCommunitiesStats(GRN, outputFolder = ".", plotAsPDF=FALSE)
2264 2280
 #' @export
2265 2281
 plotCommunitiesStats <- function(GRN, outputFolder = NULL, basenameOutput = NULL, 
2266 2282
                                  display = "byRank", communities = seq_len(10), 
... ...
@@ -2430,7 +2446,7 @@ plotCommunitiesStats <- function(GRN, outputFolder = NULL, basenameOutput = NULL
2430 2446
 #' @examples 
2431 2447
 #' # See the Workflow vignette on the GRaNIE website for examples
2432 2448
 #' GRN = loadExampleObject()
2433
-#' GRN = plotCommunitiesEnrichment(GRN, outputFolder = ".", forceRerun = FALSE)
2449
+#' GRN = plotCommunitiesEnrichment(GRN, outputFolder = ".", plotAsPDF=FALSE)
2434 2450
 #' @export
2435 2451
 #' @import ggplot2
2436 2452
 #' @importFrom grid gpar
... ...
@@ -2520,9 +2536,9 @@ plotCommunitiesEnrichment <- function(GRN, outputFolder = NULL, basenameOutput =
2520 2536
     vertexMetadata = as.data.frame(igraph::vertex.attributes(GRN@graph$TF_gene$graph))
2521 2537
     # Get the number of vertexes per community as additional annotation column for the heatmap
2522 2538
     geneCounts = vertexMetadata %>%
2523
-      dplyr::select(name, community) %>%
2539
+      dplyr::select(.data$name, .data$community) %>%
2524 2540
       dplyr::distinct() %>%
2525
-      dplyr::count(community)
2541
+      dplyr::count(.data$community)
2526 2542
     
2527 2543
     
2528 2544
     allOntologies = .checkEnrichmentCongruence_general_community(GRN, type = "community")
... ...
@@ -2604,16 +2620,19 @@ plotCommunitiesEnrichment <- function(GRN, outputFolder = NULL, basenameOutput =
2604 2620
         tibble::column_to_rownames("Term") %>%
2605 2621
         as.matrix()
2606 2622
       
2607
-      # Common heatmap parameters for both p1 and p2
2623
+ 
2608 2624
       geneCounts_communities = geneCounts %>%
2609
-        dplyr::filter(community %in% as.character(colnames(matrix.m))) %>%
2610
-        dplyr::slice(match(communities.order[-1], geneCounts$community)) %>%
2611
-        dplyr::pull(n)
2612
-        
2625
+        dplyr::filter(community %in% as.character(colnames(matrix.m)),
2626
+                      community %in% geneCounts$community) %>%
2627
+        dplyr::arrange(dplyr::desc(.data$n))
2613 2628
       
2629
+      # Sanity check
2630
+      stopifnot(identical(as.character(geneCounts_communities$community), colnames(matrix.m)[-1]))
2631
+        
2632
+      # Common heatmap parameters for both p1 and p2
2614 2633
       top_annotation = ComplexHeatmap::HeatmapAnnotation(
2615 2634
         nGenes = ComplexHeatmap::anno_barplot(
2616
-          x = c(sum(geneCounts$n), geneCounts_communities), 
2635
+          x = c(sum(geneCounts$n), geneCounts_communities$n), 
2617 2636
           border = FALSE,  bar_width = 0.8,  gp = grid::gpar(fill = "#046C9A")),
2618 2637
         annotation_name_gp = grid::gpar(fontsize=9), annotation_name_side = "left", annotation_name_rot = 90)
2619 2638
       
... ...
@@ -2634,7 +2653,7 @@ plotCommunitiesEnrichment <- function(GRN, outputFolder = NULL, basenameOutput =
2634 2653
       # Now focus on the top X only per community
2635 2654
       ID_subset =  GRN@stats$Enrichment$byCommunity[["combined"]][[ontologyCur]] %>% 
2636 2655
         dplyr::group_by(community) %>% 
2637
-        dplyr::arrange(pval) %>% 
2656
+        dplyr::arrange(.data$pval) %>% 
2638 2657
         dplyr::slice(seq_len(nID)) %>%
2639 2658
         dplyr::pull(ID) %>% as.character()
2640 2659
       
... ...
@@ -2741,7 +2760,7 @@ plotCommunitiesEnrichment <- function(GRN, outputFolder = NULL, basenameOutput =
2741 2760
 #' @examples 
2742 2761
 #' # See the Workflow vignette on the GRaNIE website for examples
2743 2762
 #' GRN = loadExampleObject()
2744
-#' GRN = plotTFEnrichment(GRN, n = 5, outputFolder = ".", forceRerun = FALSE)
2763
+#' GRN = plotTFEnrichment(GRN, n = 5, outputFolder = ".", plotAsPDF=FALSE)
2745 2764
 #' @export
2746 2765
 #' @importFrom grid gpar
2747 2766
 plotTFEnrichment <- function(GRN, rankType = "degree", n = NULL, TF.names = NULL,
... ...
@@ -2904,7 +2923,7 @@ plotTFEnrichment <- function(GRN, rankType = "degree", n = NULL, TF.names = NULL
2904 2923
       # Make sure the top annotation has the same dimensionality as the resulting matrix
2905 2924
       nodeDegree_TFset_numbers =  nodeDegree_TFset %>%
2906 2925
         dplyr::filter(TF.name %in% colnames(matrix.m)) %>%
2907
-        dplyr::arrange(desc(nodeDegree)) %>%
2926
+        dplyr::arrange(dplyr::desc(nodeDegree)) %>%
2908 2927
         dplyr::pull(nodeDegree)
2909 2928
       
2910 2929
       top_annotation = ComplexHeatmap::HeatmapAnnotation(
... ...
@@ -40,6 +40,6 @@ Run the activator-repressor classification for the TFs for a \code{\linkS4class{
40 40
 }
41 41
 \examples{
42 42
 # See the Workflow vignette on the GRaNIE website for examples
43
-GRN = loadExampleObject()
44
-GRN = AR_classification_wrapper(GRN, outputFolder = ".", forceRerun = FALSE)
43
+# GRN = loadExampleObject()
44
+# GRN = AR_classification_wrapper(GRN, outputFolder = ".", forceRerun = FALSE)
45 45
 }
... ...
@@ -50,5 +50,6 @@ Add peak-gene connections to a \code{\linkS4class{GRN}} object
50 50
 \examples{
51 51
 # See the Workflow vignette on the GRaNIE website for examples
52 52
 GRN = loadExampleObject()
53
-GRN = addConnections_peak_gene(GRN, promoterRange = 10000, outputFolder = ".")
53
+types =  list(c("protein_coding"))
54
+GRN = addConnections_peak_gene(GRN, promoterRange=10000, outputFolder=".", plotGeneTypes=types)
54 55
 }
... ...
@@ -4,12 +4,12 @@
4 4
 \alias{changeOutputDirectory}
5 5
 \title{Change the output directory of a GRN object}
6 6
 \usage{
7
-changeOutputDirectory(GRN, outputDirectory)
7
+changeOutputDirectory(GRN, outputDirectory = ".")
8 8
 }
9 9
 \arguments{
10 10
 \item{GRN}{Object of class \code{\linkS4class{GRN}}}
11 11
 
12
-\item{outputDirectory}{}
12
+\item{outputDirectory}{Character. Default \code{.}. New output directory for all output files unless overwritten via the parameter \code{outputFolder}.}
13 13
 }
14 14
 \value{
15 15
 The same \code{\linkS4class{GRN}} object, with the output directory being adjusted accordingly
... ...
@@ -18,6 +18,6 @@ The same \code{\linkS4class{GRN}} object, with the output directory being adjust
18 18
 Change the output directory of a GRN object
19 19
 }
20 20
 \examples{
21
-# GRN = loadExampleObject()
22
-# GRN = changeOutputDirectory(GRN, ".")
21
+GRN = loadExampleObject()
22
+GRN = changeOutputDirectory(GRN, outputDirectory = ".")
23 23
 }
... ...
@@ -47,6 +47,6 @@ Essentially, this functions calls \code{\link{filterGRNAndConnectGenes}} repeate
47 47
 \examples{
48 48
 # See the Workflow vignette on the GRaNIE website for examples
49 49
 GRN = loadExampleObject()
50
-GRN = generateStatsSummary(GRN, forceRerun = FALSE)
50
+GRN = generateStatsSummary(GRN, TF_peak.fdr = c(0.01, 0.1), peak_gene.fdr = c(0.01, 0.1))
51 51
 
52 52
 }
... ...
@@ -22,5 +22,5 @@ Retrieve parameters for previously used function calls and general parameters fo
22 22
 \examples{
23 23
 # See the Workflow vignette on the GRaNIE website for examples
24 24
 GRN = loadExampleObject()
25
-getParameters(GRN, type = "parameter", name = "all")
25
+params.l = getParameters(GRN, type = "parameter", name = "all")
26 26
 }
... ...
@@ -55,6 +55,6 @@ A convenience function that calls all network-related functions in one-go, using
55 55
 }
56 56
 \examples{
57 57
 # See the Workflow vignette on the GRaNIE website for examples
58
-GRN = loadExampleObject()
59
-GRN = performAllNetworkAnalyses(GRN, outputFolder = ".", forceRerun = FALSE)
58
+# GRN = loadExampleObject()
59
+# GRN = performAllNetworkAnalyses(GRN, outputFolder = ".", forceRerun = FALSE)
60 60
 }
... ...
@@ -62,5 +62,5 @@ Similarly to \code{\link{plotGeneralEnrichment}}, the results of the community-b
62 62
 \examples{
63 63
 # See the Workflow vignette on the GRaNIE website for examples
64 64
 GRN = loadExampleObject()
65
-GRN = plotCommunitiesEnrichment(GRN, outputFolder = ".", forceRerun = FALSE)
65
+GRN = plotCommunitiesEnrichment(GRN, outputFolder = ".", plotAsPDF=FALSE)
66 66
 }
... ...
@@ -50,7 +50,7 @@ Similarly to the statistics produced by \code{\link{plotGeneralGraphStats}}, sum
50 50
 \examples{
51 51
 # See the Workflow vignette on the GRaNIE website for examples
52 52
 GRN = loadExampleObject()
53
-GRN = plotCommunitiesStats(GRN, outputFolder = ".", forceRerun = FALSE)
53
+GRN = plotCommunitiesStats(GRN, outputFolder = ".", plotAsPDF=FALSE)
54 54
 }
55 55
 \seealso{
56 56
 \code{\link{plotGeneralGraphStats}}
... ...
@@ -9,6 +9,8 @@ plotDiagnosticPlots_TFPeaks(
9 9
   outputFolder = NULL,
10 10
   basenameOutput = NULL,
11 11
   plotDetails = FALSE,
12
+  plotPermuted = TRUE,
13
+  nTFMax = NULL,
12 14
   forceRerun = FALSE
13 15
 )
14 16
 }
... ...
@@ -21,16 +23,20 @@ plotDiagnosticPlots_TFPeaks(
21 23
 
22 24
 \item{plotDetails}{\code{TRUE} or \code{FALSE}. Default \code{FALSE}. Print additional plots that may help for debugging and QC purposes? Note that these plots are currently less documented or not at all.}
23 25
 
26
+\item{plotPermuted}{\code{TRUE} or \code{FALSE}. Default  \code{TRUE}. Also produce the diagnostic plots for permuted data?}
27
+
28
+\item{nTFMax}{\code{NULL} or Integer. Default \code{NULL}. Maximum number of TFs to process. Can be used for testing purposes by setting this to a small number i(.e., 10)}
29
+
24 30
 \item{forceRerun}{\code{TRUE} or \code{FALSE}. Default \code{FALSE}. Force execution, even if the GRN object already contains the result. Overwrites the old results.}
25 31
 }
26 32
 \value{
27 33
 The same \code{\linkS4class{GRN}} object, with added data from this function.
28 34
 }
29 35
 \description{
30
-Plot diagnostic plots for TF-peak connections for a \code{\linkS4class{GRN}} object
36
+Due to the number of plots that this functions produces, we currently provide only the option to plot as PDF. This may change in the future.
31 37
 }
32 38
 \examples{
33 39
 # See the Workflow vignette on the GRaNIE website for examples
34 40
 GRN = loadExampleObject()
35
-GRN = plotDiagnosticPlots_TFPeaks(GRN, outputFolder = ".", forceRerun = FALSE)
41
+GRN = plotDiagnosticPlots_TFPeaks(GRN, outputFolder = ".", plotPermuted = FALSE, nTFMax = 2)
36 42
 }
... ...
@@ -50,5 +50,6 @@ Plot diagnostic plots for peak-gene connections for a \code{\linkS4class{GRN}} o
50 50
 \examples{
51 51
 # See the Workflow vignette on the GRaNIE website for examples
52 52
 # GRN = loadExampleObject()
53
-# GRN = plotDiagnosticPlots_peakGene(GRN, outputFolder = ".", forceRerun = FALSE)
53
+# types = list(c("protein_coding"))
54
+# GRN = plotDiagnosticPlots_peakGene(GRN, outputFolder=".", gene.types=types, plotAsPDF=FALSE)
54 55
 }
... ...
@@ -50,5 +50,5 @@ This function plots the results of the general enrichment analysis for every spe
50 50
 \examples{
51 51
 # See the Workflow vignette on the GRaNIE website for examples
52 52
 GRN = loadExampleObject()
53
-GRN = plotGeneralEnrichment(GRN, outputFolder = ".", forceRerun = FALSE)
53
+GRN = plotGeneralEnrichment(GRN, outputFolder = ".", plotAsPDF=FALSE)
54 54
 }
... ...
@@ -38,7 +38,7 @@ This function generates graphical summaries about the structure and connectivity
38 38
 \examples{
39 39
 # See the Workflow vignette on the GRaNIE website for examples
40 40
 GRN = loadExampleObject()
41
-GRN = plotGeneralGraphStats(GRN, outputFolder = ".", forceRerun = FALSE)
41
+GRN = plotGeneralGraphStats(GRN, outputFolder = ".", plotAsPDF=FALSE)
42 42
 }
43 43
 \seealso{
44 44
 \code{\link{plotGeneralEnrichment}}
... ...
@@ -44,5 +44,5 @@ Produce a PCA plot of the data from a \code{\linkS4class{GRN}} object
44 44
 \examples{
45 45
 # See the Workflow vignette on the GRaNIE website for examples
46 46
 GRN = loadExampleObject()
47
-GRN = plotPCA_all(GRN, topn = 500, outputFolder = ".", forceRerun = FALSE)
47
+GRN = plotPCA_all(GRN, topn = 500, outputFolder = ".", type = "rna", plotAsPDF=FALSE)
48 48
 }
... ...
@@ -65,7 +65,7 @@ This function plots the enrichment results. The result consist of a dot plot per
65 65
 \examples{
66 66
 # See the Workflow vignette on the GRaNIE website for examples
67 67
 GRN = loadExampleObject()
68
-GRN = plotTFEnrichment(GRN, n = 5, outputFolder = ".", forceRerun = FALSE)
68
+GRN = plotTFEnrichment(GRN, n = 5, outputFolder = ".", plotAsPDF=FALSE)
69 69
 }
70 70
 \seealso{
71 71
 \code{\link{calculateTFEnrichment}}
... ...
@@ -41,5 +41,5 @@ Plot various network connectivity summaries for a \code{\linkS4class{GRN}} objec
41 41
 \examples{
42 42
 # See the Workflow vignette on the GRaNIE website for examples
43 43
 GRN = loadExampleObject()
44
-GRN = plot_stats_connectionSummary(GRN, outputFolder = ".", forceRerun = FALSE)
44
+GRN = plot_stats_connectionSummary(GRN, outputFolder = ".", forceRerun = FALSE, plotAsPDF=FALSE)
45 45
 }