gsva_data: Pathway analysis with the GSVA package

In espors/idepGolem: Integrated Differential Expression and Pathway Analysis

Pathway analysis with the GSVA package

Description

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

Usage

gsva_data(
  processed_data,
  gene_sets,
  my_range,
  pathway_p_val_cutoff,
  n_pathway_show,
  algorithm = "gsva"
)

Arguments

processed_data	Matrix of gene data that has been through pre_process()
gene_sets	List of vectors with each vector being the set of genes that correspond to a particular pathway in the database. See returned list from read_gene_sets()
my_range	Vector of the (min_set_size, max_set_size)
pathway_p_val_cutoff	Significant p-value to determine enriched pathways
n_pathway_show	Number of significant pathways to show
algorithm	Options for GSVA: plage, ssgsea, zscore or gsva

Value

A list with a data frame and a numeric value that is used in the plot_gsva() to create a heatmap.

See Also

Other pathway functions: fgsea_data(), find_overlap(), gage_data(), get_gsva_plot_data(), get_pathway_list_data(), get_pgsea_plot_all_samples_data(), get_pgsea_plot_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.