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) .


jrSiCKLSNMF

This package contains code to run joint graph-regularized single-cell Kullback-Leibler Non-negative Matrix Factorization

To install:

install.packages("devtools")
devtools::install_github("ellisdoro/jrSiCKLSNMF")

R-CMD-check

Reference manual

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install.packages("jrSiCKLSNMF")

1.2.4 by Dorothy Ellis, 5 months ago


Browse source code at https://github.com/cran/jrSiCKLSNMF


Authors: Dorothy Ellis [aut, cre] (ORCID: , Susmita Datta [ths] , Kenneth Perkins [ctb] (Util.h function author , http://programmingnotes.org/) , Renaud Gaujoux [ctb] (Author of .nndsvd R adaptation)


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, igraph, umap, kknn, ggplot2, methods, stats, rlang, Matrix, data.table, parallel, pbapply, cluster, MASS, clValid, factoextra, foreach, irlba, bluster, Rdpack, ggrepel

Suggests knitr, rmarkdown

Linking to Rcpp, RcppArmadillo, RcppProgress


See at CRAN