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:
Downloads:
Reverse dependencies:
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