'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.