Plot the results of the over-representation analysis

plot_ora() produces useful plots to visualize the results of the over-representation analysis.

Usage

plot_ora(enrichment, protein_list, pval_lim = 0.05, ncateg = 10, fontsize = 10)

Arguments

enrichment

The results of the over-representation analysis.

protein_list

A character vector containing the protein names. It should be the same as the one used in do_ora().

pval_lim

The p-value threshold to consider a term as significant.

ncateg

The number of categories to show in the plots.

fontsize

The font size for the plots.

Value

A list containing the plots.

Examples

# Perform Differential Expression Analysis
control = c("BRC", "CLL", "CRC", "CVX", "ENDC", "GLIOM", "LUNGC", "LYMPH", "MYEL", "OVC", "PRC")
de_res <- do_limma(example_data,
                   example_metadata,
                   case = "AML",
                   control = control,
                   wide = FALSE)
#> Comparing AML with BRC, CLL, CRC, CVX, ENDC, GLIOM, LUNGC, LYMPH, MYEL, OVC, PRC.

# Extract the up-regulated proteins for AML
sig_up_proteins_aml <- de_res$de_results |>
  dplyr::filter(sig == "significant up") |>
  dplyr::pull(Assay)

# Perform ORA with GO database
enrichment <- do_ora(sig_up_proteins_aml, database = "GO")
#> No background provided. When working with Olink data it is recommended to use background.
#> 'select()' returned 1:1 mapping between keys and columns

# Plot the results
plot_ora(enrichment, sig_up_proteins_aml, pval_lim = 0.05, ncateg = 5)
#> 'select()' returned 1:1 mapping between keys and columns
#> $dotplot

#> 
#> $barplot

#> 
#> $cnetplot

#>