getProbMatrix

Getter function for the cell composition matrix. This function allows to
access to the cell composition matrix of simulated mixed transcriptional
profiles.

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

getProbMatrix function

<dl><dt>object</dt>
<dd><code>SpatialDDLS</code> object with
<code>prob.cell.types</code> slot.</dd>
<dt>type.data</dt>
<dd>Subset of data to return: <code>train</code> or <code>test</code>.</dd></dl>

Arguments

Getter function for the cell composition matrix — getProbMatrix

<dl>

<dt>object</dt>
<dd><code>SpatialDDLS</code> object with
<code>prob.cell.types</code> slot.</dd>


<dt>type.data</dt>
<dd>Subset of data to return: <code>train</code> or <code>test</code>.</dd>

</dl>

getProbMatrix: Getter function for the cell composition matrix

Description

Usage

Value

Arguments

See Also