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 |
|
---|---|
Author | 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) |
Maintainer | Dorothy Ellis <ddemoreellis@gmail.com> |
License | GPL-3 |
Version | 1.2.3 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.