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 |
| DOI: |
10.32614/CRAN.package.aPEAR |
| Author: |
Ieva Kerseviciute 
[aut, cre],
Juozas Gordevicius
[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 |