prob.cell.types

prob.cell.types,SpatialDDLS-method

prob.cell.types&lt;-

prob.cell.types&lt;-,SpatialDDLS-method

Get and set <code>prob.cell.types</code> slot in a
<code>SpatialDDLS</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

prob.cell.types function

<dl><dt>object</dt>
<dd><code>SpatialDDLS</code> object.</dd>
<dt>type.data</dt>
<dd>Type of data to return. It can be <code>'both'</code> (default),
<code>'train'</code>, or <code>'test'</code>.</dd>
<dt>value</dt>
<dd>List with two <code>PropCellTypes</code> objects
corresponding to train and test data.</dd></dl>

Arguments

Get and set prob.cell.types slot in a
SpatialDDLS object — prob.cell.types

<dl>

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


<dt>type.data</dt>
<dd>Type of data to return. It can be <code>'both'</code> (default),
<code>'train'</code>, or <code>'test'</code>.</dd>


<dt>value</dt>
<dd>List with two <code>PropCellTypes</code> objects
corresponding to train and test data.</dd>

</dl>

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

Description

Usage

Arguments