cell.names

cell.names,PropCellTypes-method

cell.names&lt;-

cell.names&lt;-,PropCellTypes-method

Get and set <code>cell.names</code> slot in a
<code>PropCellTypes</code> object

Deconvolution of spatial transcriptomics data based on neural networks and single-cell RNA-seq data. SpatialDDLS implements a workflow to create neural network models able to make accurate estimates of cell composition of spots from spatial transcriptomics data using deep learning and the meaningful information provided by single-cell RNA-seq data. See Torroja and Sanchez-Cabo (2019) <doi:10.3389/fgene.2019.00978> and Mañanes et al. (2024) <doi:10.1093/bioinformatics/btae072> to get an overview of the method and see some examples of its performance.

Diego Ma<c3><b1>anes

SpatialDDLS

Deconvolution of Spatial Transcriptomics Data Based on Neural
Networks

Diego Mañanes

Carlos Torroja

Fatima Sanchez-Cabo

cell.names function

<dl><dt>object</dt>
<dd><code>PropCellTypes</code> object.</dd>
<dt>value</dt>
<dd>Matrix containing names of the mixed transcriptional profiles to
be simulated as rows and cells to be used to simulate them as columns.</dd></dl>

Arguments

Get and set cell.names slot in a
PropCellTypes object — cell.names

<dl>

<dt>object</dt>
<dd><code>PropCellTypes</code> object.</dd>


<dt>value</dt>
<dd>Matrix containing names of the mixed transcriptional profiles to
be simulated as rows and cells to be used to simulate them as columns.</dd>

</dl>

cell.names: Get and set `cell.names` slot in a `PropCellTypes` object

Description

Usage

Arguments