Multimodal Single-Cell Omics Dimensionality Reduction R package jrSiCKLSNMF version 1.2.4 Methods to perform Joint graph Regularized Single-Cell Kullback-Leibler Sparse Non-negative Matrix Factorization ('jrSiCKLSNMF', pronounced "junior sickles NMF") on quality controlled single-cell multimodal omics count data. 'jrSiCKLSNMF' specifically deals with dual-assay scRNA-seq and scATAC-seq data. This package contains functions to extract meaningful latent factors that are shared across omics modalities. These factors enable accurate cell-type clustering and facilitate visualizations. Methods for pre-processing, clustering, and mini-batch updates and other adaptations for larger datasets are also included. For further details on the methods used in this package please see Ellis, Roy, and Datta (2023) <doi:10.3389/fgene.2023.1179439>. Software Depends: R (>= 3.5.0) Imports: Rcpp (>= 1.0.9), igraph, umap, kknn, ggplot2, methods, stats, rlang, Matrix, data.table,parallel,pbapply,cluster,MASS,clValid,factoextra, foreach,irlba,bluster,Rdpack,ggrepel LinkingTo: Rcpp, RcppArmadillo, RcppProgress Suggests: knitr, rmarkdown Dorothy Ellis <ddemoreellis@gmail.com> Comprehensive R Archive Network (CRAN) Dorothy Ellis [aut, cre] (ORCID: <https://orcid.org/0000-0002-8624-0042>), Susmita Datta [ths], Kenneth Perkins [ctb] (Util.h function author, http://programmingnotes.org/), Renaud Gaujoux [ctb] (Author of .nndsvd R adaptation) GPL-3 2026-05-15 application/tgz https://CRAN.R-project.org/package=jrSiCKLSNMF doi:10.32614/CRAN.package.jrSiCKLSNMF