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jrSiCKLSNMF
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Install from CRAN:
install.packages("jrSiCKLSNMF")
Install from Github:
library("remotes")
install_github("cran/jrSiCKLSNMF") Install by package version:
library("remotes")
install_version("jrSiCKLSNMF", "1.2.3") Attach the package and use:
library("jrSiCKLSNMF")
Maintained by
Dorothy Ellis
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First Published: 2023-07-06
Latest Update: 2025-07-11
Description:
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) .
How to cite:
Dorothy Ellis (2023). jrSiCKLSNMF: Multimodal Single-Cell Omics Dimensionality Reduction. R package version 1.2.3, https://cran.r-project.org/web/packages/jrSiCKLSNMF. Accessed 30 Jul. 2026.
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Complete documentation for jrSiCKLSNMF
Functions, R codes and Examples using
the jrSiCKLSNMF R package
Some associated functions: AddSickleJrMetadata . BuildKNNGraphLaplacians . BuildSNNGraphLaplacians . CalculateUMAPSickleJr . ClusterSickleJr . CreateSickleJr . DetermineClusters . DetermineDFromIRLBA . GenerateWmatricesandHmatrix . MinibatchDiagnosticPlot . NormalizeCountMatrices . PlotLossvsLatentFactors . PlotSickleJrUMAP . RunjrSiCKLSNMF . SetLambdasandRowReg . SetWandHfromWHinitials . SickleJr-class . SimData . SimSickleJrSmall . jrSiCKLSNMF .
Some associated R codes: Data.R . RcppExports.R . jrSiCKLSNMF.R . jrSiCKLSNMFDataPreparation.R . Full jrSiCKLSNMF package functions and examples
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