DetermineDFromIRLBA

This generates v+1 plots, where v is the number of data modalities, of the approximate
singular values generated by IRLBA.There is one plot for each modality and then a
final plot that concatenates all of the modalities together. Choose the largest elbow
value among the three plots.

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>.

Dorothy Ellis

jrSiCKLSNMF

Multimodal Single-Cell Omics Dimensionality Reduction

Susmita Datta

Kenneth Perkins

Renaud Gaujoux

DetermineDFromIRLBA function

<dl><dt>SickleJr</dt>
<dd>An object of class SickleJr</dd>
<dt>d</dt>
<dd>Number of desired factors; it is important to select a number that
allows you to see a clear elbow: defaults to 50.</dd></dl>

Arguments

Create elbow plots of the singular values derived from IRLBA
to determine D for large datasets — DetermineDFromIRLBA

<dl>

<dt>SickleJr</dt>
<dd>An object of class SickleJr</dd>


<dt>d</dt>
<dd>Number of desired factors; it is important to select a number that
allows you to see a clear elbow: defaults to 50.</dd>

</dl>

DetermineDFromIRLBA: Create elbow plots of the singular values derived from IRLBA to determine D for large datasets

Description

Usage

Value

Arguments

References

Examples