Package: MOFSR Type: Package Title: Multi-Omics Fusion for Subtype Recognition Version: 2.3.0 Author: Zaoqu Liu [aut, cre] () Maintainer: Zaoqu Liu Authors@R: c( person("Zaoqu", "Liu", email = "liuzaoqu@163.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0452-742X")) ) Description: A comprehensive toolkit for integrating multi-modal biological data to discover disease subtypes and biological mechanisms. MOFSR provides 15 state-of-the-art multi-omics clustering algorithms (SNF, wSNF, CPCA, iClusterBayes, IntNMF, LRAcluster, MCIA, MOFA, NEMO, PINSPlus, RGCCA, SGCCA, CIMLR, BCC, LateFusion), 17 classification methods, parallel computing support, comprehensive visualization (UMAP, heatmaps, survival curves), data preprocessing (normalization, filtering, batch correction, QC), feature selection with bootstrap validation, and cluster quality assessment. All core algorithms are implemented internally for maximum compatibility, cross-platform support, and optimized performance. Works on Windows, macOS, and Linux without external dependencies for core functionality. License: GPL (>= 3) URL: https://zaoqu-liu.github.io/MOFSR/, https://github.com/Zaoqu-Liu/MOFSR BugReports: https://github.com/Zaoqu-Liu/MOFSR/issues Encoding: UTF-8 LazyData: true Depends: R (>= 4.1.0) Imports: stats, graphics, utils, dplyr Suggests: testthat (>= 3.0.0), knitr, rmarkdown, bench, ggplot2, glmnet, nnet, e1071, randomForest, xgboost, survival, survminer, tibble, GSVA, BiocManager, BiocGenerics, BiocParallel, Hmisc, MASS, adabag, caret, furrr, future, future.apply, gbm, mlr3, mlr3learners, progress, purrr, rpart, stringr, ssgsea.GBM.classification, class, parallel RoxygenNote: 7.3.3 Config/testthat/edition: 3 VignetteBuilder: knitr Repository: https://zaoqu-liu.r-universe.dev Date/Publication: 2026-08-11 11:48:49 UTC RemoteUrl: https://github.com/Zaoqu-Liu/MOFSR RemoteRef: master RemoteSha: 12026a8ab3fc8d745acd3b2aef937f777a03a46e NeedsCompilation: no Packaged: 2026-10-11 16:00:38 UTC; root