performAllNetworkAnalyses.RdA convenience function that calls all network-related functions in one-go, using selected default parameters and a set of adjustable ones also.
For full adjustment, run the individual functions separately.
This function requires a filtered set of connections in the GRN object as generated by filterGRNAndConnectGenes
performAllNetworkAnalyses(
GRN,
ontology = c("GO_BP", "GO_MF"),
algorithm = "weight01",
statistic = "fisher",
background = "neighborhood",
clustering = "louvain",
communities = NULL,
selection = "byRank",
topnGenes = 20,
topnTFs = 20,
maxWidth_nchar_plot = 50,
display_pAdj = FALSE,
outputFolder = NULL,
forceRerun = FALSE
)Object of class GRN
Character vector of ontologies. Default c("GO_BP", "GO_MF").
Valid values are "GO_BP", "GO_MF", "GO_CC", "KEGG", "DO", and "Reactome",
referring to GO Biological Process, GO Molecular Function, GO Cellular Component, KEGG, Disease Ontology,
and Reactome Pathways, respectively. GO ontologies require the topGO,
"KEGG" the clusterProfiler, "DO" the DOSE, and "Reactome" the ReactomePA packages, respectively.
As they are listed under Suggests, they may not yet be installed, and the function will throw an error if they are missing.
Character. Default "weight01". One of: "classic", "elim", "weight", "weight01", "lea", "parentchild". Only relevant if ontology is GO related (GO_BP, GO_MF, GO_CC), ignored otherwise. Name of the algorithm that handles the GO graph structures. Valid inputs are those supported by the topGO library.
For general information about the algorithms, see https://academic.oup.com/bioinformatics/article/22/13/1600/193669. weight01 is a mixture between the elim and the weight algorithms.
Character. Default "fisher". One of: "fisher", "ks", "t". Statistical test to be used. Only relevant if ontology is GO related (GO_BP, GO_MF, GO_CC), and valid inputs are a subset of those supported by the topGO library (we had to remove some as they do not seem to work properly in topGO either), ignored otherwise. For the other ontologies the test statistic is always Fisher.
Character. Default "neighborhood". One of: "all_annotated", "all_RNA", "all_RNA_filtered", "neighborhood". Set of genes to be used to construct the background for the enrichment analysis. This can either be all annotated genes in the reference genome (all_annotated), all genes from the provided RNA data (all_RNA), all genes from the provided RNA data excluding those marked as filtered after executing filterData (all_RNA_filtered), or all the genes that are within the neighborhood of any peak (before applying any filters except for the user-defined promoterRange value in addConnections_peak_gene) (neighborhood).
Character. Default louvain. One of: louvain, leiden, leading_eigen, fast_greedy, optimal, walktrap. The community detection algorithm to be used. Please bear in mind the robustness and time consumption of the algorithms when opting for an alternative to the default.
NULL or numeric vector or character vector. Default NULL.
If set to NULL, all community enrichments that have been calculated before are plotted.
If a numeric vector is specified (when selection = "byRank"), the rank of the communities is specified.
For example, communities = c(1,4) then denotes the first and fourth largest community.
If a character vector is specified (when selection = "byLabel"), the name of the communities is specified instead.
For example, communities = c("1","4") then denotes the communities with the names "1" and "4", which may or may not be the largest and fourth largest communities among all.
Character. Default "byRank". One of: "byRank", "byLabel".
Specify whether the communities will be selected based on their rank or explicitly by their label.
Note that the label is independent of the rank. When set to "byRank", the largest
community (with most vertices) always has a rank of 1.
Integer > 0. Default 20. Number of genes to plot, sorted by their rank or label.
Integer > 0. Default 20. Number of TFs to plot, sorted by their rank or label.
Integer (>=10). Default 50. Maximum number of characters for a term before it is truncated.
TRUE or FALSE. Default FALSE. Is the p-value being displayed in the plots the adjusted p-value? This parameter is relevant for KEGG, Disease Ontology, and Reactome enrichments, and does not affect GO enrichments.
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.
TRUE or FALSE. Default FALSE. Force execution, even if the GRN object already contains the result. Overwrites the old results.
An updated GRN object, with added data from this function.
# See the Workflow vignette on the GRaNIE website for examples
# GRN = loadExampleObject()
# GRN = performAllNetworkAnalyses(GRN, outputFolder = ".", forceRerun = FALSE)