CreateSickleJr

Using a list of sparse count matrices, create an object of class SickleJr
and specify the names of these count matrices.

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

CreateSickleJr function

<dl><dt>count.matrices</dt>
<dd>A list of quality-controlled count matrices with pre-filtered features where each modality corresponds to each matrix in the
list</dd>
<dt>names</dt>
<dd>Optional parameter with names for the count matrices in vector format</dd></dl>

Arguments

Create an object of class SickleJr — CreateSickleJr

<dl>

<dt>count.matrices</dt>
<dd>A list of quality-controlled count matrices with pre-filtered features where each modality corresponds to each matrix in the
list</dd>


<dt>names</dt>
<dd>Optional parameter with names for the count matrices in vector format</dd>

</dl>

CreateSickleJr: Create an object of class SickleJr

Description

Usage

Value

Arguments

Examples