aPEAR: 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) <doi:10.1101/2023.03.28.534514>).

Version: 1.0.0
Depends: R (≥ 3.5.0)
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 (≥ 3.0.0), knitr, rmarkdown, stringr
Published: 2023-06-12
Author: Ieva Kerseviciute ORCID iD [aut, cre], Juozas Gordevicius ORCID iD [ths], VUGENE, LLC [cph, fnd]
Maintainer: Ieva Kerseviciute <kerseviciute.ieva at gmail.com>
BugReports: https://gitlab.com/vugene/aPEAR/-/issues
License: MIT + file LICENSE
URL: https://gitlab.com/vugene/aPEAR
NeedsCompilation: no
Citation: aPEAR citation info
Materials: README NEWS
CRAN checks: aPEAR results

Documentation:

Reference manual: aPEAR.pdf
Vignettes: An introduction to _aPEAR_

Downloads:

Package source: aPEAR_1.0.0.tar.gz
Windows binaries: r-prerel: aPEAR_1.0.0.zip, r-release: aPEAR_1.0.0.zip, r-oldrel: aPEAR_1.0.0.zip
macOS binaries: r-prerel (arm64): aPEAR_1.0.0.tgz, r-release (arm64): aPEAR_1.0.0.tgz, r-oldrel (arm64): aPEAR_1.0.0.tgz, r-prerel (x86_64): aPEAR_1.0.0.tgz, r-release (x86_64): aPEAR_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=aPEAR to link to this page.