run_pathfindR: Wrapper Function for pathfindR - Active-Subnetwork-Oriented...

In pathfindR: Enrichment Analysis Utilizing Active Subnetworks

Wrapper Function for pathfindR - Active-Subnetwork-Oriented Enrichment Workflow

Description

run_pathfindR is the wrapper function for the pathfindR workflow

Usage

run_pathfindR(
  input,
  gene_sets = "KEGG",
  min_gset_size = 10,
  max_gset_size = 300,
  custom_genes = NULL,
  custom_descriptions = NULL,
  pin_name_path = "Biogrid",
  p_val_threshold = 0.05,
  enrichment_threshold = 0.05,
  convert2alias = TRUE,
  plot_enrichment_chart = TRUE,
  output_dir = NULL,
  list_active_snw_genes = FALSE,
  ...
)

Arguments

input	the input data that pathfindR uses. The input must be a data frame with three columns: Gene Symbol (Gene Symbol) Change value, e.g. log(fold change) (OPTIONAL) p value, e.g. adjusted p value associated with differential expression
gene_sets	Name of the gene sets to be used for enrichment analysis. Available gene sets are 'KEGG', 'Reactome', 'BioCarta', 'GO-All', 'GO-BP', 'GO-CC', 'GO-MF', 'cell_markers', 'mmu_KEGG' or 'Custom'. If 'Custom', the arguments custom_genes and custom_descriptions must be specified. (Default = 'KEGG')
min_gset_size	minimum number of genes a term must contain (default = 10)
max_gset_size	maximum number of genes a term must contain (default = 300)
custom_genes	a list containing the genes involved in each custom term. Each element is a vector of gene symbols located in the given custom term. Names should correspond to the IDs of the custom terms.
custom_descriptions	A vector containing the descriptions for each custom term. Names of the vector should correspond to the IDs of the custom terms.
pin_name_path	Name of the chosen PIN or absolute/path/to/PIN.sif. If PIN name, must be one of c('Biogrid', 'STRING', 'GeneMania', 'IntAct', 'KEGG', 'mmu_STRING'). If path/to/PIN.sif, the file must comply with the PIN specifications. (Default = 'Biogrid')
p_val_threshold	the p value threshold to use when filtering the input data frame. Must a numeric value between 0 and 1. (default = 0.05)
enrichment_threshold	adjusted-p value threshold used when filtering enrichment results (default = 0.05)
convert2alias	boolean to indicate whether or not to convert gene symbols in the input that are not found in the PIN to an alias symbol found in the PIN (default = TRUE) IMPORTANT NOTE: the conversion uses human gene symbols/alias symbols.
plot_enrichment_chart	boolean value. If TRUE, a bubble chart displaying the enrichment results is plotted. (default = TRUE)
output_dir	the directory to be created where the output and intermediate files are saved (default = NULL, a temporary directory is used)
list_active_snw_genes	boolean value indicating whether or not to report the non-significant active subnetwork genes for the active subnetwork which was enriched for the given term with the lowest p value (default = FALSE)
...	additional arguments for active_snw_enrichment_wrapper

Details

This function takes in a data frame consisting of Gene Symbol, log-fold-change and adjusted-p values. After input testing, any gene symbols that are not in the PIN are converted to alias symbols if the alias is in the PIN. Next, active subnetwork search is performed. Enrichment analysis is performed using the genes in each of the active subnetworks. Terms with adjusted-p values lower than enrichment_threshold are discarded. The lowest adjusted-p value (over all subnetworks) for each term is kept. This process of active subnetwork search and enrichment is repeated for a selected number of iterations, which is done in parallel. Over all iterations, the lowest and the highest adjusted-p values, as well as number of occurrences are reported for each enriched term.

Value

Data frame of pathfindR enrichment results. Columns are:

ID

ID of the enriched term

Term_Description

Description of the enriched term

Fold_Enrichment

Fold enrichment value for the enriched term (Calculated using ONLY the input genes)

occurrence

the number of iterations that the given term was found to enriched over all iterations

support

the median support (proportion of active subnetworks leading to enrichment within an iteration) over all iterations

lowest_p

the lowest adjusted-p value of the given term over all iterations

highest_p

the highest adjusted-p value of the given term over all iterations

non_Signif_Snw_Genes (OPTIONAL)

the non-significant active subnetwork genes, comma-separated

Up_regulated

the up-regulated genes (as determined by ‘change value' > 0, if the 'change column' was provided) in the input involved in the given term’s gene set, comma-separated. If change column not provided, all affected are listed here.

Down_regulated

the down-regulated genes (as determined by ‘change value' < 0, if the 'change column' was provided) in the input involved in the given term’s gene set, comma-separated

The function also creates an HTML report with the pathfindR enrichment results linked to the visualizations of the enriched terms in addition to the table of converted gene symbols. This report can be found in 'output_dir/results.html' under the current working directory.

By default, a bubble chart of top 10 enrichment results are plotted. The x-axis corresponds to fold enrichment values while the y-axis indicates the enriched terms. Sizes of the bubbles indicate the number of significant genes in the given terms. Color indicates the -log10(lowest-p) value; the more red it is, the more significant the enriched term is. See enrichment_chart.

Warning

Especially depending on the protein interaction network, the algorithm and the number of iterations you choose, 'active subnetwork search + enrichment' component of run_pathfindR may take a long time to finish.

See Also

input_testing for input testing, input_processing for input processing, active_snw_search for active subnetwork search and subnetwork filtering, enrichment_analyses for enrichment analysis (using the active subnetworks), summarize_enrichment_results for summarizing the active-subnetwork-oriented enrichment results, annotate_term_genes for annotation of affected genes in the given gene sets, visualize_terms for visualization of enriched terms, enrichment_chart for a visual summary of the pathfindR enrichment results, foreach for details on parallel execution of looping constructs, cluster_enriched_terms for clustering the resulting enriched terms and partitioning into clusters.

Examples

## Not run: 
run_pathfindR(example_pathfindR_input)

## End(Not run)

pathfindR documentation built on Oct. 9, 2023, 1:07 a.m.