visualize_terms: Create Diagrams for Enriched Terms

In egeulgen/pathfindR: Enrichment Analysis Utilizing Active Subnetworks

Create Diagrams for Enriched Terms

Description

Create Diagrams for Enriched Terms

Usage

visualize_terms(
  result_df,
  input_processed = NULL,
  is_KEGG_result = TRUE,
  pin_name_path = "Biogrid",
  ...
)

Arguments

result_df	Data frame of enrichment results. Must-have columns for KEGG human pathway diagrams (is_KEGG_result = TRUE) are: 'ID' and 'Term_Description'. Must-have columns for the rest are: 'Term_Description', 'Up_regulated' and 'Down_regulated'
input_processed	input data processed via input_processing, not necessary when is_KEGG_result = FALSE
is_KEGG_result	boolean to indicate whether KEGG gene sets were used for enrichment analysis or not (default = TRUE)
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')
...	additional arguments for visualize_KEGG_diagram (used when is_KEGG_result = TRUE) or visualize_term_interactions (used when is_KEGG_result = FALSE)

Details

For is_KEGG_result = TRUE, KEGG pathway diagrams are created, affected nodes colored by up/down regulation status. For other gene sets, interactions of affected genes are determined (via a shortest-path algorithm) and are visualized (colored by change status) using igraph.

Value

Depending on the argument is_KEGG_result, creates visualization of interactions of genes involved in the list of enriched terms in result_df. Returns a list of ggplot objects named by Term ID.

See Also

See visualize_KEGG_diagram for the visualization function of KEGG diagrams. See visualize_term_interactions for the visualization function that generates diagrams showing the interactions of input genes in the PIN. See run_pathfindR for the wrapper function of the pathfindR workflow.

Examples

## Not run: 
input_processed <- data.frame(
  GENE = c("PARP1", "NDUFA1", "STX6", "SNAP23"),
  CHANGE = c(1.5, -2, 3, 5)
)
result_df <- example_pathfindR_output[1:2, ]

gg_list <- visualize_terms(result_df, input_processed)
gg_list2 <- visualize_terms(result_df, is_KEGG_result = FALSE, pin_name_path = 'IntAct')

## End(Not run)

egeulgen/pathfindR documentation built on Feb. 19, 2025, 12:14 p.m.