Releases: egeulgen/pathfindR
Releases · egeulgen/pathfindR
pathfindR 1.5.0.9007
- added new visualization type for
UpSet_plot()
- fixed an issue with file naming on Windows in
visualize_term_interactions()
pathfindR 1.5.0.9006
fixed issue in term_gene_heatmap()
pathfindR 1.5.0.9005
Merge pull request #37 from rix133/master Fixing the Windows save problem
pathfindR v1.4.2
Minor changes and bug fixes
- Fixed corner case in
create_kappa_matrix()
whenchance
is 1, the metric is turned into 0 - Fixed misused
class(.) == *
incluster_graph_vis()
pathfindR v1.4.1
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 behaviour: 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
tovisualize_hsa_KEGG()
and torun_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 ofrun_pathfindR()
as downloading the png files is slow. - Fixed links to visualizations in
enriched_ters.Rmd
pathfindR 1.4.0
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()
andvisualize_pws()
were renamed to
annotate_term_DEGs()
,score_terms()
,cluster_enriched_terms()
,fuzzy_term_clustering()
,hierarchical_term_clustering()
,visualize_term_interactions()
andvisualize_terms()
respectively - The Rmd template file for the report
enriched_pathways.Rmd
was renamed toenriched_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()
andenrichment_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
infetch_gene_set()
andrun_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 viafilterActiveSnws()
now serves the threshold proportion of significant genes in the active subnetwork. e.g., if there are 100 significant genes andsig_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 usingKEGGREST
andKEGGgraph
Minor changes and bug fixes
- In
hierarchical_term_clustering()
, redefined the distance measure as1 - 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()
andinput_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 argumentsnum_bubbles
(default is 4) to control number of bubbles displayed in the legend andeven_breaks
(default isTRUE
) 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
inrun_pathfindR()
andinput_processing()
was renamed asconvert2alias
- 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
toenrichment_chart()
, controlling the number top enriched terms to plot (default is 10) - Other minor bug/error fixes
pathfindR 1.3.0
Major Changes
- Separated the steps of the function
run_pathfindR
into individual functions:active_snw_search
,enrichment_analyses
,summarize_enrichment_results
,annotate_pathway_DEGs
,visualize_pws
. - renamed the function
pathmap
asvisualize_hsa_KEGG
, updated the function to produce different visualizations for inputs with binary change values (ordered) and no change values (theinput_processing
function, assigns a change value of 100 to all). - Created new the visualization function
visualize_pw_interactions
, which creates PNG files visualizing the interactions (in the selected PIN) of genes involved in the given pathways. - Added new vignette, describing the step-by-step execution of the pathfindR workflow
- Changed clustering metric to kappa statistic, created the new clustering related functions
create_kappa_matrix
,hierarchical_pw_clustering
,fuzzy_pw_clustering
andcluster_pathways
. - Implemented the new function
cluster_graph_vis
for visualing graph diagrams of clustering results.
Minor changes and bug fixes
- Fixed the bug where the arguments
score_quan_thr
andsig_gene_thr
forrun_pathfindR
were not being utilized. - in
run_pathfindR
, added message at the end of run, reporting the number enriched pathways. - the function
run_pathfindR
now creates a variableorg_dir
that is the "path/to/original/working/directory".org_dir
is used in multiple funtions to return to the original working directory if anything fails. This changes the previous behavior where if a function stopped with an error the directory was changed to "..", i.e. the parent directory. This change was adapted so that the user is returned to the original working directory if they supply a recursive output folder (output_dir
, e.g. "./ALL_RESULTS/RESULT_A"). - in
input_processing
, added the argumenthuman_genes
to only perform alias symbol conversion when human gene symbols are provided. - Updated the Rmd files used to create the report HTML files - Added the data for
GO-All
, all annotations in the GO database (BP+MF+CC) - Updated the vignette
pathfindR - An R Package for Pathway Enrichment Analysis Utilizing Active Subnetworks
to reflect the new functionalities.