View source: R/calculate_kegg_enrichment.R
calculate_kegg_enrichment | R Documentation |
Analyses enrichment of KEGG pathways associated with proteins in the fraction of significant proteins compared to all detected proteins. A Fisher's exact test is performed to test significance of enrichment.
calculate_kegg_enrichment( data, protein_id, is_significant, pathway_id = pathway_id, pathway_name = pathway_name, plot = TRUE, plot_cutoff = "adj_pval top10" )
data |
a data frame that contains at least the input variables. |
protein_id |
a character column in the |
is_significant |
a logical column in the |
pathway_id |
a character column in the |
pathway_name |
a character column in the |
plot |
a logical value indicating whether the result should be plotted or returned as a table. |
plot_cutoff |
a character value indicating if the plot should contain the top 10 most
significant proteins (p-value or adjusted p-value), or if a significance cutoff should be used
to determine the number of GO terms in the plot. This information should be provided with the
type first followed by the threshold separated by a space. Example are
|
A bar plot displaying negative log10 adjusted p-values for the top 10 enriched pathways.
Bars are coloured according to the direction of the enrichment. If plot = FALSE
, a data
frame is returned.
# Load libraries library(dplyr) set.seed(123) # Makes example reproducible # Create example data kegg_data <- fetch_kegg(species = "eco") if (!is.null(kegg_data)) { # only proceed if information was retrieved data <- kegg_data %>% group_by(uniprot_id) %>% mutate(significant = rep(sample( x = c(TRUE, FALSE), size = 1, replace = TRUE, prob = c(0.2, 0.8) ), n = n() )) # Plot KEGG enrichment calculate_kegg_enrichment( data, protein_id = uniprot_id, is_significant = significant, pathway_id = pathway_id, pathway_name = pathway_name, plot = TRUE, plot_cutoff = "pval 0.05" ) # Calculate KEGG enrichment kegg <- calculate_kegg_enrichment( data, protein_id = uniprot_id, is_significant = significant, pathway_id = pathway_id, pathway_name = pathway_name, plot = FALSE ) head(kegg, n = 10) }
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