plot_barplot | R Documentation |
Plots barplot of p-values.
plot_barplot(
reshaped_results,
ontology_id_colname = "ontology_id",
selected_rows_to_plot = NULL,
p_value_type_colname = "eFDR",
p_value_max_threshold = 0.05
)
reshaped_results |
'data.table' in relaxed form, obtained as the
output of the |
ontology_id_colname |
Character, specifies the column name that contains ontology IDs in the input data. |
selected_rows_to_plot |
A numeric vector specifying which rows of the reshaped results 'data.frame' should be included in the plot. Default is 'NULL'. |
p_value_type_colname |
Character, specifies the column name for p-values in the input data. Default is 'eFDR'. |
p_value_max_threshold |
Numeric, representing the maximum p-value threshold for filtering data. Default is 0.05. |
Create a customized barplot of p-values, facilitating visual exploration and analysis of statistical significance within ontology categories.
Returns a barplot.
reshape_results
library(mulea)
# loading and filtering the example ontology from a GMT file
tf_gmt <- read_gmt(file = system.file(package="mulea", "extdata",
"Transcription_factor_RegulonDB_Escherichia_coli_GeneSymbol.gmt"))
tf_gmt_filtered <- filter_ontology(gmt = tf_gmt, min_nr_of_elements = 3,
max_nr_of_elements = 400)
# loading the example data
sign_genes <- readLines(system.file(package = "mulea", "extdata",
"target_set.txt"))
background_genes <- readLines(system.file(
package="mulea", "extdata", "background_set.txt"))
# creating the ORA model
ora_model <- ora(gmt = tf_gmt_filtered,
# the test set variable
element_names = sign_genes,
# the background set variable
background_element_names = background_genes,
# the p-value adjustment method
p_value_adjustment_method = "eFDR",
# the number of permutations
number_of_permutations = 10000,
# the number of processor threads to use
nthreads = 2)
# running the ORA
ora_results <- run_test(ora_model)
# reshaping results for visualisation
ora_reshaped_results <- reshape_results(model = ora_model,
model_results = ora_results,
# choosing which column to use for the indication of significance
p_value_type_colname = "eFDR")
# Plot barplot
plot_barplot(reshaped_results = ora_reshaped_results,
# the column containing the names we wish to plot
ontology_id_colname = "ontology_id",
# upper threshold for the value indicating the significance
p_value_max_threshold = 0.05,
# column that indicates the significance values
p_value_type_colname = "eFDR")
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