plotTrainingHistory

Plot training history of a trained DigitalDLSorter Deep Neural Network model.

Deconvolution of bulk RNA-Seq data using context-specific deconvolution models based on Deep Neural Networks using scRNA-Seq data as input. These models are able to make accurate estimates of the cell composition of bulk RNA-Seq samples from the same context using the advances provided by Deep Learning and the meaningful information provided by scRNA-Seq data. See Torroja and Sanchez-Cabo (2019) <doi:10.3389/fgene.2019.00978> for more details.

Diego Ma<c3><b1>anes

digitalDLSorteR

Deconvolution of Bulk RNA-Seq Data Based on Deep Learning

Diego Mañanes

Carlos Torroja

Fatima Sanchez-Cabo

plotTrainingHistory function

<dl><dt>object</dt>
<dd><code>DigitalDLSorter</code> object with
<code>trained.model</code> slot.</dd>
<dt>title</dt>
<dd>Title of plot.</dd>
<dt>metrics</dt>
<dd>Metrics to be plotted. If <code>NULL</code> (by default), all
metrics available in the <code>DigitalDLSorterDNN</code> object
will be plotted.</dd></dl>

Arguments

Plot training history of a trained DigitalDLSorter Deep Neural Network model — plotTrainingHistory

<dl>

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


<dt>title</dt>
<dd>Title of plot.</dd>


<dt>metrics</dt>
<dd>Metrics to be plotted. If <code>NULL</code> (by default), all
metrics available in the <code>DigitalDLSorterDNN</code> object
will be plotted.</dd>

</dl>

plotTrainingHistory: Plot training history of a trained DigitalDLSorter Deep Neural Network model

Description

Usage

Value

Arguments

See Also