CePa: Centrality-Based Pathway Enrichment

It aims to find significant pathways through network topology information. It has several advantages compared with current pathway enrichment tools. First, pathway node instead of single gene is taken as the basic unit when analysing networks to meet the fact that genes must be constructed into complexes to hold normal functions. Second, multiple network centrality measures are applied simultaneously to measure importance of nodes from different aspects to make a full view on the biological system. CePa extends standard pathway enrichment methods, which include both over-representation analysis procedure and gene-set analysis procedure. <doi:10.1093/bioinformatics/btt008>.

Version: 0.8.0
Depends: R (≥ 3.6.0)
Imports: igraph (≥ 0.6), stats, graphics, methods, grDevices, parallel, Rgraphviz, graph
Published: 2022-06-11
Author: Zuguang Gu ORCID iD [aut, cre]
Maintainer: Zuguang Gu <z.gu at dkfz.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/jokergoo/CePa
NeedsCompilation: no
CRAN checks: CePa results


Reference manual: CePa.pdf
Vignettes: CePa Vignette


Package source: CePa_0.8.0.tar.gz
Windows binaries: r-devel: CePa_0.8.0.zip, r-release: CePa_0.8.0.zip, r-oldrel: CePa_0.8.0.zip
macOS binaries: r-release (arm64): CePa_0.8.0.tgz, r-oldrel (arm64): CePa_0.8.0.tgz, r-release (x86_64): CePa_0.8.0.tgz, r-oldrel (x86_64): CePa_0.8.0.tgz
Old sources: CePa archive


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