@@ -60,7 +60,8 @@ Imports:

     graphics,

     magrittr,

     tibble,

-    viridis

+    viridis,

+    BiocFileCache

 Depends:

     R (>= 4.1.0),

     tidyverse,

@@ -34,6 +34,7 @@ export(plotGeneralGraphStats)

 export(plotPCA_all)

 export(plotTFEnrichment)

 export(plot_stats_connectionSummary)

+import(BiocFileCache)

 import(BiocManager)

 import(GenomicRanges)

 import(checkmate)

@@ -248,9 +248,9 @@ setMethod("show",

 #' @return Integer. Number of peaks that are defined in the \code{\linkS4class{GRN}} object, either by excluding (filter = TRUE) or including (filter = FALSE) peaks that are currently marked as \emph{filtered}.

 #' @examples

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # nPeaks(GRN, filter = TRUE)

-#' # nPeaks(GRN, filter = FALSE)

+#' GRN = loadExampleObject()

+#' nPeaks(GRN, filter = TRUE)

+#' nPeaks(GRN, filter = FALSE)

 #' @export

 #' @aliases peaks

 #' @rdname peaks-methods

@@ -283,9 +283,9 @@ nPeaks <- function(GRN, filter = TRUE) {

 #' @return Integer. Number of genes that are defined in the \code{\linkS4class{GRN}} object, either by excluding (filter = TRUE) or including (filter = FALSE) genes that are currently marked as \emph{filtered}.

 #' @examples

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # nGenes(GRN, filter = TRUE)

-#' # nGenes(GRN, filter = FALSE)

+#' GRN = loadExampleObject()

+#' nGenes(GRN, filter = TRUE)

+#' nGenes(GRN, filter = FALSE)

 #' @export

 #' @aliases genes

 #' @rdname genes-methods

@@ -117,9 +117,9 @@ initializeGRN <- function(objectMetadata = list(),

 #' # rna.df   = read_tsv("https://www.embl.de/download/zaugg/GRaNIE/rna.tsv.gz")

 #' # peaks.df = read_tsv("https://www.embl.de/download/zaugg/GRaNIE/peaks.tsv.gz")

 #' # meta.df  = read_tsv("https://www.embl.de/download/zaugg/GRaNIE/sampleMetadata.tsv.gz")

-#' # GRN = loadExampleObject()

+#' GRN = loadExampleObject()

 #' # We omit sampleMetadata = meta.df here, lines becomes too long otherwise

-#' # GRN = addData(GRN, counts_peaks = peaks.df, counts_rna = rna.df, forceRerun = FALSE)

+#' GRN = addData(GRN, counts_peaks = peaks.df, counts_rna = rna.df, forceRerun = FALSE)

 addData <- function(GRN, counts_peaks, normalization_peaks = "DESeq_sizeFactor", idColumn_peaks = "peakID", 

                     counts_rna, normalization_rna = "quantile", idColumn_RNA = "ENSEMBL", sampleMetadata = NULL,

@@ -602,8 +602,8 @@ addData <- function(GRN, counts_peaks, normalization_peaks = "DESeq_sizeFactor",

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = filterData(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = filterData(GRN, forceRerun = FALSE)

 #' @export

 filterData <- function (GRN, 

                         minNormalizedMean_peaks = 5, maxNormalizedMean_peaks = NULL, 

@@ -970,8 +970,8 @@ addTFBS <- function(GRN, motifFolder, TFs = "all", nTFMax = NULL, filesTFBSPatte

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function. 

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = overlapPeaksAndTFBS(GRN, nCores = 2, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = overlapPeaksAndTFBS(GRN, nCores = 2, forceRerun = FALSE)

 #' @export

 overlapPeaksAndTFBS <- function(GRN, nCores = 2, forceRerun = FALSE) {

@@ -1506,8 +1506,8 @@ importTFData <- function(GRN, data, name, idColumn = "ENSEMBL", nameColumn = "TF

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.  TF_classification_densityPlotsForegroundBackground_expression_perm{0,1}.pdf, TF_classification_stringencyThresholds_expression_perm0.pdf, TF_classification_summaryHeatmap_expression_perm0.pdf,

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = AR_classification_wrapper(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = AR_classification_wrapper(GRN, forceRerun = FALSE)

 #' @export

 AR_classification_wrapper<- function (GRN, significanceThreshold_Wilcoxon = 0.05, 

                                       plot_minNoTFBS_heatmap = 100, deleteIntermediateData = TRUE,

@@ -1724,8 +1724,8 @@ AR_classification_wrapper<- function (GRN, significanceThreshold_Wilcoxon = 0.05

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.  TF_peak.fdrCurves_perm{o,1}.pdf

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = addConnections_TF_peak(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = addConnections_TF_peak(GRN, forceRerun = FALSE)

 #' @export

 addConnections_TF_peak <- function (GRN, plotDiagnosticPlots = TRUE, plotDetails = FALSE, outputFolder = NULL, 

                                     corMethod = "pearson", 

@@ -2270,8 +2270,8 @@ addConnections_TF_peak <- function (GRN, plotDiagnosticPlots = TRUE, plotDetails

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function in different flavors.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = addConnections_peak_gene(GRN, promoterRange = 10000, nCores = 2, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = addConnections_peak_gene(GRN, promoterRange = 10000, nCores = 2, forceRerun = FALSE)

 addConnections_peak_gene <- function(GRN, overlapTypeGene = "TSS", corMethod = "pearson",

                                      promoterRange = 250000, TADs = NULL,

                                      nCores = 4, 

@@ -2812,8 +2812,8 @@ addConnections_peak_gene <- function(GRN, overlapTypeGene = "TSS", corMethod = "

 #' @return The same \code{\linkS4class{GRN}} object, with the filtered and merged TF-peak and peak-gene connections in the slot connections$all.filtered. The filtered

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = filterGRNAndConnectGenes(GRN)

+#' GRN = loadExampleObject()

+#' GRN = filterGRNAndConnectGenes(GRN)

 #' @seealso \code{\link{visualizeGRN}}

 #' @seealso \code{\link{addConnections_TF_peak}} 

 #' @seealso \code{\link{addConnections_peak_gene}} 

@@ -3387,8 +3387,8 @@ filterGRNAndConnectGenes <- function(GRN,

 #' @return  The same \code{\linkS4class{GRN}} object, with added data from this function.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = add_TF_gene_correlation(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = add_TF_gene_correlation(GRN, forceRerun = FALSE)

 add_TF_gene_correlation <- function(GRN, corMethod = "pearson", addRobustRegression = FALSE, nCores = 1, forceRerun = FALSE) {

   GRN = .addFunctionLogToObject(GRN)    

@@ -3637,8 +3637,8 @@ addSNPOverlap <- function(grn, SNPData, col_chr = "chr", col_pos = "pos", col_pe

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = generateStatsSummary(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = generateStatsSummary(GRN, forceRerun = FALSE)

 #' 

 generateStatsSummary <- function(GRN, 

                                  TF_peak.fdr = c(0.001, 0.01, 0.05, 0.1, 0.2),

@@ -3905,18 +3905,39 @@ generateStatsSummary <- function(GRN,

 #' Load example GRN dataset

 #' 

 #' @export

+#' @param forceDownload \code{TRUE} or \code{FALSE}. Default \code{FALSE}. Should the download be enforced even if the local cached file is already present?

+#' @param fileURL Character. Default https://www.embl.de/download/zaugg/GRaNIE/GRN.rds. URL to the GRN example object in rds format.

 #' @examples 

 #' GRN = loadExampleObject()

 #' @return 

 #' An example \code{\linkS4class{GRN}} object

-loadExampleObject <- function() {

+#' @import BiocFileCache

+loadExampleObject <- function(forceDownload = FALSE, fileURL = "https://www.embl.de/download/zaugg/GRaNIE/GRN.rds") {

-    GRN_obj = "https://www.embl.de/download/zaugg/GRaNIE/GRN.rds"

-    GRN = readRDS(url(GRN_obj))

+    checkmate::assertFlag(forceDownload)

+    # Taken and modified from https://www.bioconductor.org/packages/release/bioc/vignettes/BiocFileCache/inst/doc/BiocFileCache.html

+    

+    bfc <- .get_cache()

+    

+    rid <- BiocFileCache::bfcquery(bfc, "geneFileV2", "rname")$rid

+    if (!length(rid)) {

+        rid <- names(BiocFileCache::bfcadd(bfc, "geneFileV2", fileURL))

+    }

+    if (isFALSE(BiocFileCache::bfcneedsupdate(bfc, rid)) | forceDownload) {

+        messageStr = paste0("Downloading GRaNIE example object from ", fileURL)

+        message(messageStr)

+        filePath = BiocFileCache::bfcdownload(bfc, rid, ask = FALSE)

+    }

+        

+    

+    filePath = BiocFileCache::bfcrpath(bfc, rids = rid)

+

+    # Now we can read in the locally stored file

+    readRDS(filePath)

-    GRN

 }

+

 #' Get counts for the various data defined in a \code{\linkS4class{GRN}} object

 #' 

 #' Get counts for the various data defined in a \code{\linkS4class{GRN}} object.

@@ -3929,8 +3950,8 @@ loadExampleObject <- function() {

 #' @import tibble

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = getCounts(GRN, type = "peaks", norm = TRUE, permuted = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = getCounts(GRN, type = "peaks", norm = TRUE, permuted = FALSE)

 #' @return Data frame of counts, with the type as indicated by the function parameters.

 #' getCounts(GRN, type = "peaks", norm = TRUE)

 getCounts <- function(GRN, type, norm, permuted = FALSE) {

@@ -4020,8 +4041,8 @@ getCounts <- function(GRN, type, norm, permuted = FALSE) {

 #' @return A data frame with the connections. Importantly, this function does NOT return a \code{\linkS4class{GRN}} object.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN_con.all = getGRNConnections(GRN, include_TF_gene_correlations = TRUE)

+#' GRN = loadExampleObject()

+#' GRN_con.all.df = getGRNConnections(GRN)

 getGRNConnections <- function(GRN, type = "all.filtered",  permuted = FALSE, include_TF_gene_correlations = FALSE) {

   GRN = .addFunctionLogToObject(GRN)

@@ -4198,7 +4219,7 @@ getGRNConnections <- function(GRN, type = "all.filtered",  permuted = FALSE, inc

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

+#' GRN = loadExampleObject()

 #' # getParameters(GRN, type = "parameter", name = "all")

 #' 

 getParameters <- function (GRN, type = "parameter", name = "all") {

@@ -4249,6 +4270,10 @@ getParameters <- function (GRN, type = "parameter", name = "all") {

 #' @export

 #' @template GRN

 #' @return The same \code{\linkS4class{GRN}} object, with some slots being deleted (\code{GRN@data$TFs$classification} as well as \code{GRN@stats$connectionDetails.l})

+#' @examples 

+#' # See the Workflow vignette on the GRaNIE website for examples

+#' GRN = loadExampleObject()

+#' GRN = deleteIntermediateData(GRN)

 deleteIntermediateData <- function(GRN) {

@@ -4273,23 +4298,6 @@ deleteIntermediateData <- function(GRN) {

 }

-updateGRNObject <- function(GRN) {

-  

-  # Recently created internal slot

-  if (is.null(GRN@config$parameters$internal)) {

-   

-    futile.logger::flog.info(paste0("Creating GRN@config$parameters$internal slot"))

-    GRN@config$parameters$internal = list()

-    GRN@config$parameters$internal$plot_minNoTFBS_heatmap      = GRN@config$parameters$plot_minNoTFBS_heatmap

-    GRN@config$parameters$internal$nPermutations               = GRN@config$parameters$nPermutations

-    GRN@config$parameters$internal$stepsFDR                    = GRN@config$parameters$stepsFDR

-    GRN@config$parameters$internal$allClassificationThresholds = GRN@config$parameters$allClassificationThresholds

-    GRN@config$parameters$internal$colorCategories             = GRN@config$parameters$colorCategories

-  } 

-  

-  GRN

-}

-

 .checkForbiddenNames <- function(name, forbiddenNames) {

   if (name %in% forbiddenNames) {

@@ -703,4 +703,11 @@ match.call.defaults <- function(asList = TRUE, ...) {

 #' @import utils

 is.installed <- function(mypkg){

     is.element(mypkg, installed.packages()[,1])

-} 

\ No newline at end of file

+} 

+

+# Taken from https://www.bioconductor.org/packages/release/bioc/vignettes/BiocFileCache/inst/doc/BiocFileCache.html

+.get_cache <- function() {

+    # cache <- tools::R_user_dir(utils::packageName(), which="cache")

+    cache <- tools::R_user_dir("GRaNIE", which="cache")

+    BiocFileCache::BiocFileCache(cache, ask = FALSE)

+}

@@ -10,8 +10,8 @@

 #' @export

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = build_eGRN_graph(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = build_eGRN_graph(GRN, forceRerun = FALSE)

 #' @return The same \code{\linkS4class{GRN}} object.

 build_eGRN_graph <- function(GRN, model_TF_gene_nodes_separately = FALSE, 

                              allowLoops = FALSE, removeMultiple = FALSE, directed = FALSE, forceRerun = FALSE) {

@@ -200,8 +200,8 @@ build_eGRN_graph <- function(GRN, model_TF_gene_nodes_separately = FALSE,

 #' @export

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = performAllNetworkAnalyses(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = performAllNetworkAnalyses(GRN, forceRerun = FALSE)

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.

 performAllNetworkAnalyses <- function(GRN, ontology = c("GO_BP", "GO_MF"), 

                                       algorithm = "weight01", statistic = "fisher",

@@ -297,8 +297,8 @@ performAllNetworkAnalyses <- function(GRN, ontology = c("GO_BP", "GO_MF"),

 #' @seealso \code{\link{plotCommunitiesEnrichment}}

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = calculateGeneralEnrichment(GRN, ontology = "GO_BP", forceRerun = FALSE)

+#' GRN =  loadExampleObject()

+#' GRN =  calculateGeneralEnrichment(GRN, ontology = "GO_BP", forceRerun = FALSE)

 #' @export

 #' @import topGO

 #' @import BiocManager

@@ -727,8 +727,8 @@ calculateGeneralEnrichment <- function(GRN, ontology = c("GO_BP", "GO_MF"),

 #' @import patchwork

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = calculateCommunitiesStats(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = calculateCommunitiesStats(GRN, forceRerun = FALSE)

 #' @export

 calculateCommunitiesStats <- function(GRN, clustering = "louvain", forceRerun = FALSE, ...){

@@ -810,8 +810,8 @@ calculateCommunitiesStats <- function(GRN, clustering = "louvain", forceRerun =

 #' @seealso \code{\link{calculateGeneralEnrichment}}

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = calculateCommunitiesEnrichment(GRN, ontology = c("GO_BP"), forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = calculateCommunitiesEnrichment(GRN, ontology = c("GO_BP"), forceRerun = FALSE)

 #' @export

 calculateCommunitiesEnrichment <- function(GRN, 

                                            ontology = c("GO_BP", "GO_MF"), algorithm = "weight01", 

@@ -937,9 +937,9 @@ calculateCommunitiesEnrichment <- function(GRN,

 #' @return A dataframe with the node names and the corresponding scores used to rank them

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # topGenes = getTopNodes(GRN, nodeType = "gene", rankType = "degree", n = 3)

-#' # topTFs = getTopNodes(GRN, nodeType = "TF", rankType = "EV", n = 5)

+#' GRN = loadExampleObject()

+#' topGenes = getTopNodes(GRN, nodeType = "gene", rankType = "degree", n = 3)

+#' topTFs = getTopNodes(GRN, nodeType = "TF", rankType = "EV", n = 5)

 #' @export

 getTopNodes <- function(GRN, nodeType, rankType, n = 0.1, use_TF_gene_network = TRUE) { # },

     #        TFConnectionType = "tf-gene", geneConnectionType = "peak-gene"){

@@ -1023,9 +1023,9 @@ getTopNodes <- function(GRN, nodeType, rankType, n = 0.1, use_TF_gene_network =

 #' @return The same \code{\linkS4class{GRN}} object, with the enrichment results stored in the \code{stats$Enrichment$byTF} slot.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = calculateTFEnrichment(GRN, n = 5, ontology = "GO_BP", forceRerun = FALSE)

-#' # GRN = calculateTFEnrichment(GRN, n = 5, ontology = "GO_BP", forceRerun = FALSE)

+#' GRN =  loadExampleObject()

+#' GRN =  calculateTFEnrichment(GRN, n = 5, ontology = "GO_BP", forceRerun = FALSE)

+#' GRN =  calculateTFEnrichment(GRN, n = 5, ontology = "GO_BP", forceRerun = FALSE)

 #' @export

 calculateTFEnrichment <- function(GRN, rankType = "degree", n = 0.1, TF.names = NULL,

                                   ontology = c("GO_BP", "GO_MF"), algorithm = "weight01", 

@@ -16,8 +16,8 @@

 #' @return The same \code{\linkS4class{GRN}} object, without modifications. In addition, for each specified \code{type}, a PDF file is produced with a PCA. We refer to the Vignettes for details and further explanations.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plotPCA_all(GRN, type = c("rna", "peaks"), topn = 500, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plotPCA_all(GRN, type = c("rna", "peaks"), topn = 500, forceRerun = FALSE)

 #' @export

 plotPCA_all <- function(GRN, outputFolder = NULL, basenameOutput = NULL, 

                         type = c("rna", "peaks"), topn = c(500,1000,5000), 

@@ -450,8 +450,8 @@ plotPCA_all <- function(GRN, outputFolder = NULL, basenameOutput = NULL,

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plotDiagnosticPlots_TFPeaks(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plotDiagnosticPlots_TFPeaks(GRN, forceRerun = FALSE)

 #' @export

 plotDiagnosticPlots_TFPeaks <- function(GRN, 

                                         outputFolder = NULL, 

@@ -791,8 +791,8 @@ plotDiagnosticPlots_TFPeaks <- function(GRN,

 #' @return The same \code{\linkS4class{GRN}} object, with added data from this function.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plotDiagnosticPlots_peakGene(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plotDiagnosticPlots_peakGene(GRN, forceRerun = FALSE)

 #' @export

 plotDiagnosticPlots_peakGene <- function(GRN, 

                                          outputFolder = NULL, 

@@ -1564,8 +1564,8 @@ plotDiagnosticPlots_peakGene <- function(GRN,

 #' @return The same \code{\linkS4class{GRN}} object, without modifications. In addition, for the specified \code{type}, a PDF file (default filename is GRN.connectionSummary_{type}.pdf) is produced with a connection summary. We refer to the Vignettes for details and further explanations.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plot_stats_connectionSummary(GRN, type = "heatmap", forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plot_stats_connectionSummary(GRN, type = "heatmap", forceRerun = FALSE)

 #' @export

 #' @importFrom circlize colorRamp2

 plot_stats_connectionSummary <- function(GRN, type = "heatmap", 

@@ -1893,8 +1893,8 @@ plot_stats_connectionSummary <- function(GRN, type = "heatmap",

 #' @seealso \code{\link{plotCommunitiesEnrichment}}

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plotGeneralGraphStats(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plotGeneralGraphStats(GRN, forceRerun = FALSE)

 #' @export

 plotGeneralGraphStats <- function(GRN, outputFolder = NULL, basenameOutput = NULL, 

                                   plotAsPDF = TRUE, pdf_width = 12, pdf_height = 12, 

@@ -2058,8 +2058,8 @@ plotGeneralGraphStats <- function(GRN, outputFolder = NULL, basenameOutput = NUL

 #' @return The same \code{\linkS4class{GRN}} object, without modifications. A single PDF file is produced with the results.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plotGeneralEnrichment(GRN, topn_pvalue = 30, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plotGeneralEnrichment(GRN, topn_pvalue = 30, forceRerun = FALSE)

 #' @export

 plotGeneralEnrichment <- function(GRN, outputFolder = NULL, basenameOutput = NULL, 

                                   ontology = NULL, topn_pvalue = 30, p = 0.05, 

@@ -2236,8 +2236,8 @@ plotGeneralEnrichment <- function(GRN, outputFolder = NULL, basenameOutput = NUL

 #' @seealso \code{\link{calculateCommunitiesEnrichment}}

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plotCommunitiesStats(GRN, display = "byRank", forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plotCommunitiesStats(GRN, display = "byRank", forceRerun = FALSE)

 #' @export

 plotCommunitiesStats <- function(GRN, outputFolder = NULL, basenameOutput = NULL, 

                                  display = "byRank", communities = seq_len(10), 

@@ -2405,8 +2405,8 @@ plotCommunitiesStats <- function(GRN, outputFolder = NULL, basenameOutput = NULL

 #' @return  The same \code{\linkS4class{GRN}} object, without modifications. A single PDF file is produced with the results.

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plotCommunitiesEnrichment(GRN, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plotCommunitiesEnrichment(GRN, forceRerun = FALSE)

 #' @export

 #' @import ggplot2

 #' @importFrom grid gpar

@@ -2706,8 +2706,8 @@ plotCommunitiesEnrichment <- function(GRN, outputFolder = NULL, basenameOutput =

 #' @seealso \code{\link{calculateTFEnrichment}}

 #' @examples 

 #' # See the Workflow vignette on the GRaNIE website for examples

-#' # GRN = loadExampleObject()

-#' # GRN = plotTFEnrichment(GRN, rankType = "degree", n = 5, forceRerun = FALSE)

+#' GRN = loadExampleObject()

+#' GRN = plotTFEnrichment(GRN, rankType = "degree", n = 5, forceRerun = FALSE)

 #' @export

 #' @importFrom grid gpar

 plotTFEnrichment <- function(GRN, rankType = "degree", n = NULL, TF.names = NULL,

@@ -40,6 +40,6 @@ Run the activator-repressor classification for the TFs for a \code{\linkS4class{

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = AR_classification_wrapper(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = AR_classification_wrapper(GRN, forceRerun = FALSE)

 }

@@ -52,6 +52,6 @@ Add TF-peak connections to a \code{\linkS4class{GRN}} object

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = addConnections_TF_peak(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = addConnections_TF_peak(GRN, forceRerun = FALSE)

 }

@@ -49,6 +49,6 @@ Add peak-gene connections to a \code{\linkS4class{GRN}} object

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = addConnections_peak_gene(GRN, promoterRange = 10000, nCores = 2, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = addConnections_peak_gene(GRN, promoterRange = 10000, nCores = 2, forceRerun = FALSE)

 }

@@ -50,7 +50,7 @@ Add data to a \code{\linkS4class{GRN}} object

 # rna.df   = read_tsv("https://www.embl.de/download/zaugg/GRaNIE/rna.tsv.gz")

 # peaks.df = read_tsv("https://www.embl.de/download/zaugg/GRaNIE/peaks.tsv.gz")

 # meta.df  = read_tsv("https://www.embl.de/download/zaugg/GRaNIE/sampleMetadata.tsv.gz")

-# GRN = loadExampleObject()

+GRN = loadExampleObject()

 # We omit sampleMetadata = meta.df here, lines becomes too long otherwise

-# GRN = addData(GRN, counts_peaks = peaks.df, counts_rna = rna.df, forceRerun = FALSE)

+GRN = addData(GRN, counts_peaks = peaks.df, counts_rna = rna.df, forceRerun = FALSE)

 }

@@ -31,6 +31,6 @@ Add TF-gene correlations to a \code{\linkS4class{GRN}} object. The information i

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = add_TF_gene_correlation(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = add_TF_gene_correlation(GRN, forceRerun = FALSE)

 }

@@ -34,6 +34,6 @@ Builds a graph out of a set of connections

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = build_eGRN_graph(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = build_eGRN_graph(GRN, forceRerun = FALSE)

 }

@@ -43,8 +43,8 @@ After the vertices of the filtered GRN are clustered into communities using \cod

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = calculateCommunitiesEnrichment(GRN, ontology = c("GO_BP"), forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = calculateCommunitiesEnrichment(GRN, ontology = c("GO_BP"), forceRerun = FALSE)

 }

 \seealso{

 \code{\link{plotCommunitiesEnrichment}}

@@ -23,6 +23,6 @@ This function generates the TF-gene graph from the filtered GRN object, and clus

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = calculateCommunitiesStats(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = calculateCommunitiesStats(GRN, forceRerun = FALSE)

 }

@@ -37,8 +37,8 @@ This function runs an enrichment analysis for the genes in the filtered network.

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = calculateGeneralEnrichment(GRN, ontology = "GO_BP", forceRerun = FALSE)

+GRN =  loadExampleObject()

+GRN =  calculateGeneralEnrichment(GRN, ontology = "GO_BP", forceRerun = FALSE)

 }

 \seealso{

 \code{\link{plotGeneralEnrichment}}

@@ -46,7 +46,7 @@ This function calculates the GO enrichment per TF, i.e. for the set of genes a g

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = calculateTFEnrichment(GRN, n = 5, ontology = "GO_BP", forceRerun = FALSE)

-# GRN = calculateTFEnrichment(GRN, n = 5, ontology = "GO_BP", forceRerun = FALSE)

+GRN =  loadExampleObject()

+GRN =  calculateTFEnrichment(GRN, n = 5, ontology = "GO_BP", forceRerun = FALSE)

+GRN =  calculateTFEnrichment(GRN, n = 5, ontology = "GO_BP", forceRerun = FALSE)

 }

@@ -15,3 +15,8 @@ The same \code{\linkS4class{GRN}} object, with some slots being deleted (\code{G

 \description{

 Optional convenience function to delete intermediate data from the function \link{AR_classification_wrapper} and summary statistics that may occupy a lot of space

 }

+\examples{

+# See the Workflow vignette on the GRaNIE website for examples

+GRN = loadExampleObject()

+GRN = deleteIntermediateData(GRN)

+}

@@ -55,6 +55,6 @@ Filter data from a \code{\linkS4class{GRN}} object

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = filterData(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = filterData(GRN, forceRerun = FALSE)

 }

@@ -80,8 +80,8 @@ Internally, first, the TF-peak are filtered before the peak-gene connections are

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = filterGRNAndConnectGenes(GRN)

+GRN = loadExampleObject()

+GRN = filterGRNAndConnectGenes(GRN)

 }

 \seealso{

 \code{\link{visualizeGRN}}

@@ -46,7 +46,7 @@ Essentially, this functions calls \code{filterGRNAndConnectGenes} repeatedly and

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = generateStatsSummary(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = generateStatsSummary(GRN, forceRerun = FALSE)

 }

@@ -20,7 +20,7 @@ Return the number of genes (all or only non-filtered ones) that are defined in t

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# nGenes(GRN, filter = TRUE)

-# nGenes(GRN, filter = FALSE)

+GRN = loadExampleObject()

+nGenes(GRN, filter = TRUE)

+nGenes(GRN, filter = FALSE)

 }

@@ -24,6 +24,6 @@ Get counts for the various data defined in a \code{\linkS4class{GRN}} object.

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = getCounts(GRN, type = "peaks", norm = TRUE, permuted = FALSE)

+GRN = loadExampleObject()

+GRN = getCounts(GRN, type = "peaks", norm = TRUE, permuted = FALSE)

 }

@@ -28,6 +28,6 @@ Extract connections from a \code{\linkS4class{GRN}} object

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN_con.all = getGRNConnections(GRN, include_TF_gene_correlations = TRUE)

+GRN = loadExampleObject()

+GRN_con.all.df = getGRNConnections(GRN)

 }

@@ -21,7 +21,7 @@ Retrieve parameters for previously used function calls and general parameters fo

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

+GRN = loadExampleObject()

 # getParameters(GRN, type = "parameter", name = "all")

 }

@@ -25,7 +25,7 @@ Retrieve top Nodes in the filtered \code{\linkS4class{GRN}}

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# topGenes = getTopNodes(GRN, nodeType = "gene", rankType = "degree", n = 3)

-# topTFs = getTopNodes(GRN, nodeType = "TF", rankType = "EV", n = 5)

+GRN = loadExampleObject()

+topGenes = getTopNodes(GRN, nodeType = "gene", rankType = "degree", n = 3)

+topTFs = getTopNodes(GRN, nodeType = "TF", rankType = "EV", n = 5)

 }

@@ -4,7 +4,15 @@

 \alias{loadExampleObject}

 \title{Load example GRN dataset}

 \usage{

-loadExampleObject()

+loadExampleObject(

+  forceDownload = FALSE,

+  fileURL = "https://www.embl.de/download/zaugg/GRaNIE/GRN.rds"

+)

+}

+\arguments{

+\item{forceDownload}{\code{TRUE} or \code{FALSE}. Default \code{FALSE}. Should the download be enforced even if the local cached file is already present?}

+

+\item{fileURL}{Character. Default https://www.embl.de/download/zaugg/GRaNIE/GRN.rds. URL to the GRN example object in rds format.}

 }

 \value{

 An example \code{\linkS4class{GRN}} object

@@ -21,6 +21,6 @@ Overlap peaks and TFBS for a \code{\linkS4class{GRN}} object

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = overlapPeaksAndTFBS(GRN, nCores = 2, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = overlapPeaksAndTFBS(GRN, nCores = 2, forceRerun = FALSE)

 }

@@ -20,7 +20,7 @@ Return the number of peaks (all or only non-filtered ones) that are defined in t

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# nPeaks(GRN, filter = TRUE)

-# nPeaks(GRN, filter = FALSE)

+GRN = loadExampleObject()

+nPeaks(GRN, filter = TRUE)

+nPeaks(GRN, filter = FALSE)

 }

@@ -55,6 +55,6 @@ A convenience function that calls all network-related functions in one-go, using

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = performAllNetworkAnalyses(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = performAllNetworkAnalyses(GRN, forceRerun = FALSE)

 }

@@ -61,6 +61,6 @@ Similarly to \code{\link{plotGeneralEnrichment}}, the results of the community-b

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plotCommunitiesEnrichment(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plotCommunitiesEnrichment(GRN, forceRerun = FALSE)

 }

@@ -49,8 +49,8 @@ Similarly to the statistics produced by \code{\link{plotGeneralGraphStats}}, sum

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plotCommunitiesStats(GRN, display = "byRank", forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plotCommunitiesStats(GRN, display = "byRank", forceRerun = FALSE)

 }

 \seealso{

 \code{\link{plotGeneralGraphStats}}

@@ -31,6 +31,6 @@ Plot diagnostic plots for TF-peak connections for a \code{\linkS4class{GRN}} obj

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plotDiagnosticPlots_TFPeaks(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plotDiagnosticPlots_TFPeaks(GRN, forceRerun = FALSE)

 }

@@ -49,6 +49,6 @@ Plot diagnostic plots for peak-gene connections for a \code{\linkS4class{GRN}} o

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plotDiagnosticPlots_peakGene(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plotDiagnosticPlots_peakGene(GRN, forceRerun = FALSE)

 }

@@ -49,6 +49,6 @@ This function plots the results of the general enrichment analysis for every spe

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plotGeneralEnrichment(GRN, topn_pvalue = 30, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plotGeneralEnrichment(GRN, topn_pvalue = 30, forceRerun = FALSE)

 }

@@ -37,8 +37,8 @@ This function generates graphical summaries about the structure and connectivity

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plotGeneralGraphStats(GRN, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plotGeneralGraphStats(GRN, forceRerun = FALSE)

 }

 \seealso{

 \code{\link{plotGeneralEnrichment}}

@@ -43,6 +43,6 @@ Produce a PCA plot of the data from a \code{\linkS4class{GRN}} object

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plotPCA_all(GRN, type = c("rna", "peaks"), topn = 500, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plotPCA_all(GRN, type = c("rna", "peaks"), topn = 500, forceRerun = FALSE)

 }

@@ -64,8 +64,8 @@ This function plots the enrichment results. The result consist of a dot plot per

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plotTFEnrichment(GRN, rankType = "degree", n = 5, forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plotTFEnrichment(GRN, rankType = "degree", n = 5, forceRerun = FALSE)

 }

 \seealso{

 \code{\link{calculateTFEnrichment}}

@@ -40,6 +40,6 @@ Plot various network connectivity summaries for a \code{\linkS4class{GRN}} objec

 }

 \examples{

 # See the Workflow vignette on the GRaNIE website for examples

-# GRN = loadExampleObject()

-# GRN = plot_stats_connectionSummary(GRN, type = "heatmap", forceRerun = FALSE)

+GRN = loadExampleObject()

+GRN = plot_stats_connectionSummary(GRN, type = "heatmap", forceRerun = FALSE)

 }