loadTrainedModelFromH5

Load from an HDF5 file a trained deep neural network model into a
<code>SpatialDDLS</code> object. Note that HDF5 file must be a valid
trained model (keras 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

loadTrainedModelFromH5 function

<dl><dt>object</dt>
<dd><code>SpatialDDLS</code> object with
<code>trained.model</code> slot.</dd>
<dt>file.path</dt>
<dd>Valid file path where the model are stored.</dd>
<dt>reset.slot</dt>
<dd>Deletes <code>trained.slot</code> if it already exists. A new
<code>DeconvDLModel</code> object will be formed, but will not contain
other slots (<code>FALSE</code> by default).</dd></dl>

Arguments

Load from an HDF5 file a trained deep neural network model into a
SpatialDDLS object — loadTrainedModelFromH5

<dl>

<dt>object</dt>
<dd><code>SpatialDDLS</code> object with
<code>trained.model</code> slot.</dd>


<dt>file.path</dt>
<dd>Valid file path where the model are stored.</dd>


<dt>reset.slot</dt>
<dd>Deletes <code>trained.slot</code> if it already exists. A new
<code>DeconvDLModel</code> object will be formed, but will not contain
other slots (<code>FALSE</code> by default).</dd>

</dl>

loadTrainedModelFromH5: Load from an HDF5 file a trained deep neural network model into a `SpatialDDLS` object

Description

Usage

Value

Arguments

See Also