View source: R/fct_06_pathway.R
fgsea_data | R Documentation |
Run pathway analysis with the FGSEA package using the results
from the limma_value()
.
fgsea_data(
select_contrast,
my_range,
limma,
gene_p_val_cutoff,
gene_sets,
absolute_fold,
pathway_p_val_cutoff,
n_pathway_show
)
select_contrast |
String designating the comparison from DEG analysis to
filter for the significant genes. See the 'comparison' element from the list
returned from |
my_range |
Vector of the (min_set_size, max_set_size) |
limma |
Results list from the |
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 results list from
|
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 |
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.
Other pathway functions:
find_overlap()
,
gage_data()
,
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()
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