DESCRIPTION
was updatedannotate_pathway_DEGs()
, calculate_pw_scores()
, cluster_pathways()
, fuzzy_pw_clustering()
, hierarchical_pw_clustering()
, visualize_pw_interactions()
and visualize_pws()
were renamed to annotate_term_DEGs()
, score_terms()
, cluster_enriched_terms()
, fuzzy_term_clustering()
, hierarchical_term_clustering()
, visualize_term_interactions()
and visualize_terms()
respectivelyenriched_pathways.Rmd
was renamed to enriched_terms.Rmd
term_gene_graph()
, which creates a graph of enriched terms - involved genesenrichment()
and enrichment_analyses()
to get enrichment results fasterfetch_gene_set()
for obtaining gene set data more easilymin_gset_size
, max_gset_size
in fetch_gene_set()
and run_pathfindR()
)gaCrossover
during active subnetwork search which controls the probability of a crossover in GA (default = 1, i.e. always perform crossover)testthat
create_kappa_matrix()
)mmu_kegg_genes
& mmu_kegg_descriptions
: mmu KEGG gene sets datamyeloma_input
& myeloma_output
: example mmu input and output datasig_gene_thr
in subnetwork filtering via filterActiveSnws()
now serves the threshold proportion of significant genes in the active subnetwork. e.g., if there are 100 significant genes and sig_gene_thr = 0.03
, subnetwork that contain at least 3 (100 x 0.03) significant genes will be accepted for further analysispathview
dependency by implementing colored pathway diagram visualization function using KEGGREST
and KEGGgraph
hierarchical_term_clustering()
, redefined the distance measure as 1 - kappa statistic
cluster_graph_vis()
(during the calculations for additional node colors)cluster_graph_vis()
active_snw_search()
, unnecessary warnings during active subnetwork search were removedenrichment_chart()
, supplying fuzzy clustered results no longer raises an errorinput_testing()
and input_processing()
to ensure that both the initial input data frame and the processed input data frame for active subnetwork search contain at least 2 genes (to fix the corner case encountered in issue #17)enrichment_chart()
, ensuring that bubble sizes displayed in the legend (proportional to # of DEGs) are integersenrichment_chart()
, added the arguments num_bubbles
(default is 4) to control number of bubbles displayed in the legend and even_breaks
(default is TRUE
) to indicate if even increments of breaks are requiredterm_gene_graph()
(create the igraph object as an undirected graph for better auto layout)visualize_term_interactions()
. The legend no longer displays “Non-input Active Snw. Genes” if they were not providedhuman_genes
in run_pathfindR()
and input_processing()
was renamed as convert2alias
top_terms
to enrichment_chart()
, controlling the number top enriched terms to plot (default is 10)max_to_plot
to visualize_hsa_KEGG()
and to run_pathfindR()
. This argument controls the number of pathways to be visualized (default is NULL, i.e. no filter). This was implemented not to slow down the runtime of run_pathfindR()
as downloading the png files is slow.enriched_ters.Rmd
create_kappa_matrix()
when chance
is 1, the metric is turned into 0class(.) == *
in cluster_graph_vis()