The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

enrichit: 'C++' Implementations of Functional Enrichment Analysis

Fast implementations of functional enrichment analysis methods using 'C++' via 'Rcpp'. Currently provides Over-Representation Analysis (ORA), Gene Set Enrichment Analysis (GSEA), Weighted Enrichment Analysis for ORA and GSEA, Network-based Set Enrichment Analysis (NSEA), multi-layer network-based enrichment, and multi-omics integration workflows. Additional features include early fusion at the feature level, late fusion at the pathway level, multi-omics contribution tracing, topology-aware explanation helpers, Bayesian term selection, and extremely fast Random Walk with Restart (RWR) using 'RcppEigen'. The enrichment methods build on GSEA by Subramanian et al. (2005) <doi:10.1073/pnas.0506580102>, the multilevel strategy derived from 'fgsea' by Korotkevich et al. (2021) <doi:10.1101/060012>, and network-based enrichment ideas described by Glaab et al. (2012) <doi:10.1093/bioinformatics/bts389>.

Version: 0.2.0
Depends: R (≥ 3.5.0)
Imports: Matrix, methods, Rcpp (≥ 1.0.10), rlang, stats, yulab.utils (> 0.2.1)
LinkingTo: Rcpp, RcppEigen
Suggests: AnnotationDbi, BiasedUrn, clusterProfiler, DOSE, fgsea, gson, qvalue, testthat
Published: 2026-07-01
DOI: 10.32614/CRAN.package.enrichit
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu at gmail.com>
License: Artistic-2.0
URL: https://yulab-smu.top/biomedical-knowledge-mining-book/
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: enrichit results

Documentation:

Reference manual: enrichit.html , enrichit.pdf

Downloads:

Package source: enrichit_0.2.0.tar.gz
Windows binaries: r-devel: enrichit_0.2.0.zip, r-release: enrichit_0.2.0.zip, r-oldrel: enrichit_0.1.5.zip
macOS binaries: r-release (arm64): enrichit_0.2.0.tgz, r-oldrel (arm64): enrichit_0.2.0.tgz, r-release (x86_64): enrichit_0.2.0.tgz, r-oldrel (x86_64): enrichit_0.2.0.tgz
Old sources: enrichit archive

Reverse dependencies:

Reverse imports: clusterProfiler, DOSE, enrichplot, meshes, MicrobiomeProfiler, ReactomePA, RegEnrich

Linking:

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.