Package: pathfindR 3.0.2

Ege Ulgen

pathfindR: Enrichment Analysis Utilizing Active Subnetworks

Enrichment analysis enables researchers to uncover mechanisms underlying a phenotype. However, conventional methods for enrichment analysis do not take into account protein-protein interaction information, resulting in incomplete conclusions. 'pathfindR' is a tool for enrichment analysis utilizing active subnetworks. The main function identifies active subnetworks in a protein-protein interaction network using a user-provided list of genes and associated p values. It then performs enrichment analyses on the identified subnetworks, identifying enriched terms (i.e. pathways or, more broadly, gene sets) that possibly underlie the phenotype of interest. 'pathfindR' also offers functionalities to cluster the enriched terms and identify representative terms in each cluster, to score the enriched terms per sample and to visualize analysis results. The enrichment, clustering and other methods implemented in 'pathfindR' are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2019. 'pathfindR': An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks. Front. Genet. <doi:10.3389/fgene.2019.00858>.

Authors:Ege Ulgen [cre, cph], Ozan Ozisik [aut]

pathfindR_3.0.2.tar.gz
pathfindR_3.0.2.tar.gz(r-4.7-arm64)pathfindR_3.0.2.tar.gz(r-4.7-x86_64)pathfindR_3.0.2.tar.gz(r-4.6-arm64)pathfindR_3.0.2.tar.gz(r-4.6-x86_64)
pathfindR_3.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
pathfindR/json (API)

# Install 'pathfindR' in R:
install.packages('pathfindR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/egeulgen/pathfindr/issues

Pkgdown/docs site:https://egeulgen.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

6.37 score 2 stars 314 scripts 1.5k downloads 19 mentions 35 exports 128 dependencies

Last updated from:cbbd363312. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK323
linux-devel-x86_64OK343
source / vignettesOK374
linux-release-arm64OK328
linux-release-x86_64OK355
wasm-releaseOK237

Exports:active_subnetwork_searchannotate_term_genesbuild_networkbuild_score_contextcluster_enriched_termscluster_graph_viscombine_pathfindR_resultscombined_results_graphcreate_kappa_matrixcreate_term_gene_graphcreate_term_gene_plotenrichmentenrichment_analysesenrichment_chartfetch_gene_setsfilter_active_subnetworksfuzzy_term_clusteringget_active_subnetworksget_gene_sets_listget_pin_filehierarchical_term_clusteringhyperg_testinput_processinginput_testingplot_scoresreturn_pin_pathrun_pathfindRscore_termssummarize_enrichment_resultsterm_gene_heatmapUpSet_plotvisualize_active_subnetworksvisualize_KEGG_diagramvisualize_term_interactionsvisualize_terms

Dependencies:AnnotationDbiaskpassassertthatbabelgenebase64encBiobaseBiocFileCacheBiocGenericsBiostringsbitbit64blobbslibcachemclasscliclustercodetoolscpp11crayoncurldata.tableDBIdbplyrDEoptimRdigestdiptestdoParalleldplyrevaluatefarverfastmapfilelockflexmixfontawesomefontBitstreamVerafontLiberationfontquiverforeachfpcfsgdtoolsgenericsggforceggiraphggkeggggnewscaleggplot2ggraphggrepelggupsetgluegraphlayoutsgridExtragtablehighrhtmltoolshtmlwidgetshttrhttr2igraphIRangesisobanditeratorsjquerylibjsonliteKEGGRESTkernlabknitrlabelinglatticelifecyclemagickmagrittrMASSMatrixmclustmemoisemimemodeltoolsmsigdbrnnetopensslpatchworkpathfindR.datapillarpkgconfigpngpolyclipprabcluspurrrR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRcppArmadillorlangrmarkdownrobustbaseRSQLiteS4VectorsS7sassscalesSeqinfoshadowtextstringistringrsyssystemfontstibbletidygraphtidyrtidyselecttinytextweenrutf8vctrsviridisviridisLitewithrxfunXMLXVectoryaml

Introduction to pathfindR
Overview | Active-subnetwork-oriented Enrichment Analysis | Useful arguments | Filtering Input Genes | Output Directory | Gene Sets for Enrichment | Filtering Enriched Terms by Adjusted-p Values | Protein-protein Interaction Network | Active Subnetwork Search Method | Other Arguments | Output | Enriched Terms Data Frame | HTML Report (created when output_dir is set) | Enriched Term Diagrams | Clustering Enriched Terms | Hierarchical Clustering | Heuristic Fuzzy Multiple-linkage Partitioning | Aggregated Term Scores per Sample | Comparison of 2 pathfindR Results | Analysis with Custom Gene Sets
Rendered fromintro_vignette.Rmdusingknitr::rmarkdown

Last update: 2026-06-22
Started: 2019-11-08

Visualization of pathfindR Enrichment Results
enrichment_chart(): Bubble Chart of Enrichment Results | visualize_terms(): Enriched Term Diagrams | term_gene_heatmap(): Terms by Genes Heatmap | create_term_gene_graph() & create_term_gene_plot: Term-Gene Graph | UpSet_plot(): UpSet Plots of Enriched Terms
Rendered fromvisualization_vignette.Rmdusingknitr::rmarkdown

Last update: 2026-06-22
Started: 2020-06-06

Obtaining PIN and Gene Sets Data
Get PIN File | Get Gene Sets List | KEGG Pathway Gene Sets | Reactome Pathway Gene Sets | MSigDB Gene Sets
Rendered fromobtain_data.Rmdusingknitr::rmarkdown

Last update: 2025-02-17
Started: 2020-06-06

Comparing Two pathfindR Results
Rendered fromcomparing_results.Rmdusingknitr::rmarkdown

Last update: 2023-05-06
Started: 2020-06-06

pathfindR Analysis for non-Homo-sapiens organisms
Preparation of Necessary Data | Obtain Organism-specific Gene Sets | Obtain Organism-specific Protein-protein Interaction Network | Running pathfindR on non-Homo sapiens data | Input Data | Executing run_pathfindR() | Built-in Mus musculus Data
Rendered fromnon_hs_analysis.Rmdusingknitr::rmarkdown

Last update: 2023-05-06
Started: 2019-11-08

Readme and manuals

Help Manual

Help pageTopics
Find the connected components among a set of "on" nodes.find_components_named
Find the scored subnetworks among a set of "on" nodes.find_subnetworks
Compare two individuals rank-by-rank.ga_compare
Crossover and mutation of two parent genomes.ga_crossover_mutation
Build a GA individual from a logical genome.ga_make_individual
Pick one index by rank-proportional (roulette) selection.ga_pick
Fitness of an individual.ga_score
Sort a population from best to worst.ga_sort_desc
Run the genetic-algorithm active subnetwork search.genetic_algorithm
Run the greedy active subnetwork search.greedy_search
Create a subnetwork object from a vector of node names.make_subnetwork
Parse the experiment input into a clean gene / p-value data frame.parse_experiment
Score a subnetwork from its size and z-score sum.score_subnetwork
Run the simulated annealing active subnetwork search.simulated_annealing
Sort a list of subnetwork objects by score, descending.sort_subnetworks_desc
Wrapper for Active Subnetwork Search + Enrichment over Single/Multiple Iteration(s)active_snw_enrichment_wrapper
Active subnetwork searchactive_subnetwork_search
Annotate the Affected Genes in the Provided Enriched Termsannotate_term_genes
Build the undirected interaction network from a SIF filebuild_network
Build the score contextbuild_score_context
Cluster Enriched Termscluster_enriched_terms
Graph Visualization of Clustered Enriched Termscluster_graph_vis
Color hsa KEGG pathwaycolor_kegg_pathway
Combine 2 pathfindR Resultscombine_pathfindR_results
Combined Results Graphcombined_results_graph
Create HTML Report of pathfindR Resultscreate_HTML_report
Create Kappa Statistics Matrixcreate_kappa_matrix
Create Term-Gene Graphcreate_term_gene_graph
Create Term-Gene Plotcreate_term_gene_plot
Perform Enrichment Analysis for a Single Gene Setenrichment
Perform Enrichment Analyses on the Input Subnetworksenrichment_analyses
Create Bubble Chart of Enrichment Resultsenrichment_chart
Example Unfiltered Active Subnetworksexample_unfiltered_snws
Fetch Gene Set Objectsfetch_gene_sets
Parse Active Subnetwork Search Output File and Filter the Subnetworksfilter_active_subnetworks
Heuristic Fuzzy Multiple-linkage Partitioning of Enriched Termsfuzzy_term_clustering
Get Active Subnetworksget_active_subnetworks
Retrieve the Requested Release of Organism-specific BioGRID PINget_biogrid_pin
Retrieve Organism-specific Gene Sets Listget_gene_sets_list
Retrieve Organism-specific KEGG Pathway Gene Setsget_kegg_gsets
Retrieve Organism-specific MSigDB Gene Setsget_mgsigdb_gsets
Retrieve Organism-specific PIN dataget_pin_file
Retrieve Reactome Pathway Gene Setsget_reactome_gsets
Retrieve Gene Sets from GMT-format Filegset_list_from_gmt
Hierarchical Clustering of Enriched Termshierarchical_term_clustering
Hypergeometric Distribution-based Hypothesis Testinghyperg_test
Process Inputinput_processing
Input Testinginput_testing
Check if value is a valid colorisColor
Order input data frame by provided columnnorder_df_by_columnn
pathfindR: A package for Enrichment Analysis Utilizing Active SubnetworkspathfindR-package pathfindR
Plot the Heatmap of Score Matrix of Enriched Terms per Sampleplot_scores
Process Data frame of Protein-protein Interactionsprocess_pin
Return The Path to Given Protein-Protein Interaction Network (PIN)return_pin_path
Wrapper Function for pathfindR - Active-Subnetwork-Oriented Enrichment Workflowrun_pathfindR
Safely download and parse web contentsafe_get_content
Calculate Agglomerated Scores of Enriched Terms for Each Subjectscore_terms
Active Subnetwork Search + Enrichment Analysis Wrapper for a Single Iterationsingle_iter_wrapper
Summarize Enrichment Resultssummarize_enrichment_results
Create Terms by Genes Heatmapterm_gene_heatmap
Create UpSet Plot of Enriched TermsUpSet_plot
Visualize Active Subnetworksvisualize_active_subnetworks
Visualize Human KEGG Pathwaysvisualize_KEGG_diagram
Visualize Interactions of Genes Involved in the Given Enriched Termsvisualize_term_interactions
Create Diagrams for Enriched Termsvisualize_terms