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 |
| Reference manual: | enrichit.html , enrichit.pdf |
| 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_0.2.0.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 imports: | clusterProfiler, DOSE, enrichplot, meshes, MicrobiomeProfiler, ReactomePA, RegEnrich |
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