Major Changes

• Replaced most occurrences of “pathway” to “term”. This was adapted because “term” reflects the utility of the package better. The enrichment and clustering approaches work with any kind of gene set data (be it pathway gene sets, gene ontology gene sets, motif gene sets etc.) Accordingly:
• DESCRIPTION was updated
• The functions annotate_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() respectively
• The Rmd template file for the report enriched_pathways.Rmd was renamed to enriched_terms.Rmd
• All the Rmd template files for the report were updated
• Documentation of each function was updated accordingly
• Added the visualization function term_gene_graph(), which creates a graph of enriched terms - involved genes
• Made changes in enrichment() and enrichment_analyses() to get enrichment results faster
• Added the function fetch_gene_set() for obtaining gene set data more easily
• Terms in gene sets can now be filtered according to the number of genes a term contains (controlled by min_gset_size, max_gset_size in fetch_gene_set() and run_pathfindR())
• Added the argument gaCrossover during active subnetwork search which controls the probability of a crossover in GA (default = 1, i.e. always perform crossover)
• Added unit tests using testthat
• Updated all gene sets data
• Updated all RA example data
• The vignettes were updated
• Updated all PIN data
• Improved speed of kappa matrix calculation (create_kappa_matrix())
• Added vignette for non-Homo-sapiens organisms
• Added Mus musculus (mmu) data:
• mmu_kegg_genes & mmu_kegg_descriptions: mmu KEGG gene sets data
• mmu STRING PIN
• myeloma_input & myeloma_output: example mmu input and output data
• Added the STRING PIN (combined score >= 400)
• The argument sig_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 analysis
• Removed pathview dependency by implementing colored pathway diagram visualization function using KEGGREST and KEGGgraph

Minor changes and bug fixes

• In hierarchical_term_clustering(), redefined the distance measure as 1 - kappa statistic
• Fixed minor issue in cluster_graph_vis() (during the calculations for additional node colors)
• Removed title from graph visualization of hierarchical clustering in cluster_graph_vis()
• In active_snw_search(), unnecessary warnings during active subnetwork search were removed
• Fixed minor issue in enrichment_chart(), supplying fuzzy clustered results no longer raises an error
• Added new checks in input_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)
• Fixed minor issue in enrichment_chart(), ensuring that bubble sizes displayed in the legend (proportional to # of DEGs) are integers
• In enrichment_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 required
• Updated the logo
• Minor fix in term_gene_graph() (create the igraph object as an undirected graph for better auto layout)
• Minor fix in visualize_term_interactions(). The legend no longer displays “Non-input Active Snw. Genes” if they were not provided
• The argument human_genes in run_pathfindR() and input_processing() was renamed as convert2alias
• The gene symbols in the input data frame, the PIN and the gene sets are now turned into uppercase (for obtaining the best overlap)
• Added the argument top_terms to enrichment_chart(), controlling the number top enriched terms to plot (default is 10)
• Other minor bug/error fixes

Major Changes

• Fixed error in DESCRIPTION: the Java version in SystemRequirements was corrected to “Java (>= 8.0)”
• The Java version is now checked

Minor changes and bug fixes

• Fixed behavior: when no input genes are present in the enriched hsa KEGG pathway, visualization of the pathway is now skipped
• Added the argument 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.
• Fixed links to visualizations in enriched_ters.Rmd

Minor changes and bug fixes

• Fixed corner case in create_kappa_matrix() when chance is 1, the metric is turned into 0
• Fixed misused class(.) == * in cluster_graph_vis()