# Multimodal Single-Cell Omics Dimensionality Reduction

## Documentation for package ‘jrSiCKLSNMF’ version 1.2.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

AddSickleJrMetadata | Add metadata to an object of class SickleJr
BuildKNNGraphLaplacians | Build KNN graphs and generate their graph Laplacians
BuildSNNGraphLaplacians | Build SNN graphs and generate their graph Laplacians
CalculateUMAPSickleJr | Calculate the UMAP for an object of class SickleJr
ClusterSickleJr | Cluster the \mathbf{H} matrix
CreateSickleJr | Create an object of class SickleJr
DetermineClusters | Perform clustering diagnostics
DetermineDFromIRLBA | Create elbow plots of the singular values derived from IRLBA to determine D for large datasets
GenerateWmatricesandHmatrix | Initialize the \mathbf{W} matrices in each modality and the shared \mathbf{H} matrix
jrSiCKLSNMF | Run jrSiCKLSNMF outside of a SickleJr object
MinibatchDiagnosticPlot | Plot a diagnostic plot for the mini-batch algorithm
NormalizeCountMatrices | Normalize the count matrices and set whether to use the Poisson KL divergence or the Frobenius norm
PlotLossvsLatentFactors | Create plots to help determine the number of latent factors
PlotSickleJrUMAP | Generate UMAP plots for an object of class SickleJr
RunjrSiCKLSNMF | Run jrSiCKLSNMF on an object of class SickleJr
SetLambdasandRowReg | Set lambda values and type of row regularization for an object of class SickleJr
SetWandHfromWHinitials | Set \mathbf{W} matrices and \mathbf{H} matrix from pre-calculated values
SickleJr | The SickleJr class
SickleJr-class | The SickleJr class
SimData | A simulated dataset for use with jrSiCKLSNMF
SimSickleJrSmall | A small SickleJr object containing a subset of data from the SimData data object. Contains the completed analysis from the 'Getting Started' vignette for a small subset of 10 cells with 150 genes and 700 peaks. The clusters derived from this dataset are not accurate; this dataset is intended for use with code examples.