SimSickleJrSmall: A small SickleJr object containing a subset of data from the...
In jrSiCKLSNMF: Multimodal Single-Cell Omics Dimensionality Reduction
SimSickleJrSmall R Documentation
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.
Description
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.
Usage
data(SimSickleJrSmall)
Format
A SickleJr object containing a completed analysis using jrSiCKLSNMF
- count.matrices
Contains a list of 2 sparse matrices, each containing a different
simulated omics modality measured on the same set of single cells
- normalized.count.matrices
The normalized versions of the count matrices
contained in slot count.matrices
- graph.laplacian.list
A list of sparse matrices containing the graph
Laplacians corresponding to the KNN feature-feature similarity graphs constructed
for each omics modality
- rowRegularization
A string indicating the row regularization: here it
is set to "None"
- diffFunc
A string specifying the function to measure the discrepancy
between the normalized data and the fitted matrices: here, it is set to "klp"
for the Poisson Kullback-Leibler divergence
- lambdaWlist
A list holding the graph regularization parameters: here,
they are 10 and 50
- lambdaH
A numeric indicating the value for the sparsity parameter.
Here it is equals 500
- Wlist
A list holding the fitted \mathbf{W}^v matrices
- H
A matrix holding \mathbf{H}
- WHinitials
A list of initial values for \mathbf{W}^v and \mathbf{H}
- lossCalcSubsample
A vector containing a subset on which to calculate the loss
- latent.factor.elbow.values
A data frame holding the loss and the number of latent factor that is used for diagnostic plots
- minibatch
A Boolean indicating whether or not to use the mini-batch algorithm: FALSE here
- clusterdiagnostics
Diagnostic plots and results
- clusters
A list holding the "kmeans" clustering results
- metadata
A list holding metadata; here this is just cell type information
- loss
A list holding a vector called "Loss"
- umap
A list holding various UMAP approximations
- plots
A list holding ggplots corresponding to different diagnostics and visualizations
Source
jrSiCKLSNMF documentation built on Aug. 12, 2025, 1:08 a.m.
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| SimSickleJrSmall | R Documentation |
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.
Description
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.
Usage
data(SimSickleJrSmall)
Format
A SickleJr object containing a completed analysis using jrSiCKLSNMF
- count.matrices
Contains a list of 2 sparse matrices, each containing a different simulated omics modality measured on the same set of single cells
- normalized.count.matrices
The normalized versions of the count matrices contained in slot
count.matrices- graph.laplacian.list
A list of sparse matrices containing the graph Laplacians corresponding to the KNN feature-feature similarity graphs constructed for each omics modality
- rowRegularization
A string indicating the row regularization: here it is set to
"None"- diffFunc
A string specifying the function to measure the discrepancy between the normalized data and the fitted matrices: here, it is set to "klp" for the Poisson Kullback-Leibler divergence
- lambdaWlist
A list holding the graph regularization parameters: here, they are 10 and 50
- lambdaH
A numeric indicating the value for the sparsity parameter. Here it is equals 500
- Wlist
A list holding the fitted
\mathbf{W}^vmatrices- H
A matrix holding
\mathbf{H}- WHinitials
A list of initial values for
\mathbf{W}^vand\mathbf{H}- lossCalcSubsample
A vector containing a subset on which to calculate the loss
- latent.factor.elbow.values
A data frame holding the loss and the number of latent factor that is used for diagnostic plots
- minibatch
A Boolean indicating whether or not to use the mini-batch algorithm:
FALSEhere- clusterdiagnostics
Diagnostic plots and results
- clusters
A list holding the
"kmeans"clustering results- metadata
A list holding metadata; here this is just cell type information
- loss
A list holding a vector called "Loss"
- umap
A list holding various UMAP approximations
- plots
A list holding ggplots corresponding to different diagnostics and visualizations
Source
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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