gage_data: Pathway analysis with gage package

In espors/idepGolem: Integrated Differential Expression and Pathway Analysis

Pathway analysis with gage package

Description

Run pathway analysis with the gage package using the results from the limma_value function.

Usage

gage_data(
  select_go,
  select_contrast,
  min_set_size,
  max_set_size,
  limma,
  gene_p_val_cutoff,
  gene_sets,
  absolute_fold,
  pathway_p_val_cutoff,
  n_pathway_show
)

Arguments

select_go	String designating the section of the database to query for pathway analysis. See gmt_category() for choices.
select_contrast	String designating the comparison from DEG analysis to filter for the significant genes. See the 'comparison' element from the list returned from limma_value() for options.
min_set_size	Minimum gene set size for a pathway
max_set_size	Maximum gene set size for a pathway
limma	Results list from the limma_value()
gene_p_val_cutoff	Significant p-value to filter the top genes fold change by
gene_sets	List of vectors with each vector being the set of genes that correspond to a particular pathway in the database. See list returned from read_gene_sets()
absolute_fold	TRUE/FALSE to use the absolute value of the fold change
pathway_p_val_cutoff	Significant p-value to determine enriched pathways
n_pathway_show	Number of pathways to return in final result

Value

A data frame with the results of the pathway analysis. The data frame has five columns for the direction of the regulation, the pathway description, the stat value, the number of overlapping genes, and the p-value.

See Also

Other pathway functions: fgsea_data(), find_overlap(), get_gsva_plot_data(), get_pathway_list_data(), get_pgsea_plot_all_samples_data(), get_pgsea_plot_data(), gsva_data(), kegg_pathway(), pathway_select_data(), pgsea_data(), pgsea_plot_all(), plot_gsva(), plot_pgsea(), reactome_data(), remove_pathway_id(), remove_pathway_id_second()

espors/idepGolem documentation built on April 23, 2024, 1:11 p.m.