plot_enrichment_results {XINA} | R Documentation |
Plot GO and KEGG enrichment results
plot_enrichment_results(enriched_results, term_description = "term_description", sig_score = "pvalue", num_terms = 0, get_log = TRUE, fill_color = "darkgray")
enriched_results |
GO or KEGG enrichment results. See xina_enrichment and xina_enrichment |
term_description |
Description of terms to be drawn on Y axis. Default is "term_description" of XINA enrichment results. |
sig_score |
significant score to plot on X axis. Default is "pvalue". |
num_terms |
The number of terms to be plotted. Default is 0, which menas no limit. |
get_log |
If this is TRUE, 'plot_enrichment_results' will take -log10 of p-values. |
fill_color |
Default is 'darkgray'. You can change color of bars. |
ggplot bar graph
## Not run: library(STRINGdb) # load XINA example data data(xina_example) # Get STRING database for protein-protein intereaction information string_db <- STRINGdb$new( version="10", species=9606, score_threshold=0, input_directory="" ) string_db # XINA analysis with STRING DB xina_result <- xina_analysis(example_clusters, string_db) # Select proteins that showed cluster #1 in the Stimulus2 condition subgroup <- subset(example_clusters$aligned, Stimulus2==1) protein_list <- as.vector(subgroup$`Gene name`) # Enrichment test and get significantly enriched functional terms # that have adjuseted p-value less than 0.1 kegg_enriched <- xina_enrichment(string_db, protein_list, enrichment_type = "KEGG", pval_threshold=0.1) plot_enrichment_results(kegg_enriched$KEGG, num_terms=10) ## End(Not run)