Advanced Pathway Enrichment Analysis Representation

Simplify pathway enrichment analysis results by detecting clusters of similar pathways and visualizing it as an enrichment network, where nodes and edges describe the pathways and similarity between them, respectively. This reduces the redundancy of the overlapping pathways and helps to notice the most important biological themes in the data (Kerseviciute and Gordevicius (2023) ).


aPEAR: an R package for autonomous visualisation of pathway enrichment networks

Reference manual

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install.packages("aPEAR")

1.0.0 by Ieva Kerseviciute, 3 years ago


https://gitlab.com/vugene/aPEAR


Report a bug at https://gitlab.com/vugene/aPEAR/-/issues


Browse source code at https://github.com/cran/aPEAR


Authors: Ieva Kerseviciute [aut, cre] , Juozas Gordevicius [ths] , VUGENE , LLC [cph, fnd]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports arules, bayesbio, data.table, dplyr, igraph, lsa, MCL, reshape2, tibble, utils, stats, methods, ggplot2, ggrepel, ggforce

Suggests Spectrum, clusterProfiler, gprofiler2, DOSE, org.Hs.eg.db, testthat, knitr, rmarkdown, stringr


See at CRAN