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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "enrichit" in publications use:'
type: software
license: Artistic-2.0
title: 'enrichit: ''C++'' Implementations of Functional Enrichment Analysis'
version: 0.2.0
doi: 10.32614/CRAN.package.enrichit
abstract: 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) <https://doi.org/10.1073/pnas.0506580102>, the multilevel strategy
  derived from 'fgsea' by Korotkevich et al. (2021) <https://doi.org/10.1101/060012>,
  and network-based enrichment ideas described by Glaab et al. (2012) <https://doi.org/10.1093/bioinformatics/bts389>.
authors:
- family-names: Yu
  given-names: Guangchuang
  email: guangchuangyu@gmail.com
repository: https://cran.r-universe.dev
commit: fb787911b606956438ea0245139709d1adc5214d
url: https://yulab-smu.top/biomedical-knowledge-mining-book/
date-released: '2026-07-01'
contact:
- family-names: Yu
  given-names: Guangchuang
  email: guangchuangyu@gmail.com