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)
- Version1.2.1
- R version≥ 3.5.0
- LicenseGPL-3
- Needs compilation?Yes
- jrSiCKLSNMF citation info
- Last release07/06/2023
Documentation
Team
Dorothy Ellis
Susmita Datta
Show author detailsRolesThesis advisorKenneth Perkins
Show author detailsRolesContributorRenaud Gaujoux
Show author detailsRolesContributor
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- Depends1 package
- Imports20 packages
- Suggests2 packages
- Linking To3 packages