cell.types

cell.types,DeconvDLModel-method

cell.types&lt;-

cell.types&lt;-,DeconvDLModel-method

Get and set <code>cell.types</code> slot in a
<code>DeconvDLModel</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.types function

<dl><dt>object</dt>
<dd><code>DeconvDLModel</code> object.</dd>
<dt>value</dt>
<dd>Vector with cell types considered by the deep neural network
model.</dd></dl>

Arguments

Get and set cell.types slot in a
DeconvDLModel object — cell.types

<dl>

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


<dt>value</dt>
<dd>Vector with cell types considered by the deep neural network
model.</dd>

</dl>

cell.types: Get and set `cell.types` slot in a `DeconvDLModel` object

Description

Usage

Arguments