'C++' Implementations of Functional Enrichment Analysis R package enrichit version 0.2.0 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>. Software 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 Guangchuang Yu <guangchuangyu@gmail.com> Comprehensive R Archive Network (CRAN) Guangchuang Yu [aut, cre] Artistic-2.0 2026-07-01 application/tgz https://CRAN.R-project.org/package=enrichit doi:10.32614/CRAN.package.enrichit