jrSiCKLSNMF: Multimodal Single-Cell Omics Dimensionality Reduction

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>.

Package details

AuthorDorothy 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)
MaintainerDorothy Ellis <ddemoreellis@gmail.com>
LicenseGPL-3
Version1.2.3
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("jrSiCKLSNMF")

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jrSiCKLSNMF documentation built on Aug. 12, 2025, 1:08 a.m.