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>.
|Depends:||R (≥ 3.6.0)|
|Imports:||igraph (≥ 0.6), stats, graphics, methods, grDevices, parallel, Rgraphviz, graph|
|Author:||Zuguang Gu [aut, cre]|
|Maintainer:||Zuguang Gu <z.gu at dkfz.de>|
|License:||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]|
|CRAN checks:||CePa results|
|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|
Please use the canonical form https://CRAN.R-project.org/package=CePa to link to this page.