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<h1 class="title toc-ignore">Interactive</h1>
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<p><br></p>
<div id="interactive-annotation" class="section level1">
<h1>Interactive Annotation</h1>
<p><strong>VoltRon</strong> includes interactive applications to select
and manually label spatial points by drawing polygons and circles. As an
example, we will use a Spot-based spatial transcriptomic assay,
specifically the <strong>Mouse Brain Serial Section 1/2</strong>
datasets, analyzed in the <a href="nicheclustering.html">Niche
Clustering</a> tutorial. You can find the already analyzed data stored
as a VoltRon object <a
href="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/NicheClustering/Visium&Visium_data_decon_analyzed.rds">here</a></p>
<pre class="r watch-out"><code>MBrain_Sec <- readRDS("Visium&Visium_data_decon_analyzed.rds")</code></pre>
<p>We can start annotating the spatial assay. By passing arguments used
by the <strong>vrSpatialPlot</strong> function to visualize labels
(e.g. clusters), we can better select regions within tissue sections for
annotation.</p>
<pre class="r watch-out"><code>MBrain_Sec <- annotateSpatialData(MBrain_Sec, assay = "Assay1",
group.by = "clusters", label = "annotation")</code></pre>
<p><img width="100%" height="100%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/interactive_annotation.png" class="center"></p>
<p><br></p>
<p>Here, <strong>annotateSpatialData</strong> function not only labels
spots with within regions of interests (ROIs) selected by the user, but
also records these regions in ROI assays within the same layer of the
annotated Visium assay. The new assay type will be given the name
<strong>ROIAnnotations</strong> if otherwise not specified using the
<strong>annotation_assay</strong> arguement in the function.</p>
<pre class="r watch-out"><code>MBrain_Sec </code></pre>
<pre><code>VoltRon Object
Anterior:
Layers: Section1 Section2
Posterior:
Layers: Section1 Section2
Assays: Visium_decon(Main) Visium ROIAnnotation </code></pre>
<pre class="r watch-out"><code>MBrain_Sec@sample.metadata </code></pre>
<pre><code>> MBrain_Sec@sample.metadata
Assay Layer Sample
Assay1 Visium Section1 Anterior
Assay2 Visium Section2 Anterior
Assay3 Visium Section1 Posterior
Assay4 Visium Section2 Posterior
Assay5 ROIAnnotation Section1 Anterior</code></pre>
<p>The new annotations are available in the metadata of the spot assay
(default assay in this object) and can be visualized if wanted.</p>
<pre class="r watch-out"><code>head(Metadata(MBrain_Sec))</code></pre>
<pre><code> Count Assay Layer Sample clusters annotation
AAACAAGTATCTCCCA-1_Assay1 1 Visium_decon Section1 Anterior 1 Region 3
AAACACCAATAACTGC-1_Assay1 1 Visium_decon Section1 Anterior 3 undefined
AAACAGAGCGACTCCT-1_Assay1 1 Visium_decon Section1 Anterior 4 undefined
AAACAGCTTTCAGAAG-1_Assay1 1 Visium_decon Section1 Anterior 5 Region 1
AAACAGGGTCTATATT-1_Assay1 1 Visium_decon Section1 Anterior 5 Region 1
AAACATGGTGAGAGGA-1_Assay1 1 Visium_decon Section1 Anterior 3 undefined</code></pre>
<pre class="r watch-out"><code>vrSpatialPlot(MBrain_Sec, assay = "Assay1", group.by = "annotation")</code></pre>
<p><img width="80%" height="80%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/interactive_annotation_plot.png" class="center"></p>
<p><br></p>
<p>You can also overlay the ROI annotations with the clustered spots to
visualize multiple assays in the same time.</p>
<pre class="r watch-out"><code>library(ggnewscale)
vrSpatialPlot(MBrain_Sec, assay = "Assay1", group.by = "clusters") |>
addSpatialLayer(MBrain_Sec, assay = "Assay5", group.by = "annotation", alpha = 0.7)</code></pre>
<p><img width="80%" height="80%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/interactive_annotation_example_overlay_plot.png" class="center"></p>
<p><br></p>
</div>
<div id="interactive-visualization" class="section level1">
<h1>Interactive Visualization</h1>
<p>VoltRon incorporates utilities</p>
<ul>
<li><strong>(i)</strong> to convert VoltRon objects into other spatial
data objects and files that could be used platforms, and</li>
<li><strong>(ii)</strong> to incorporate wrapper functions to call
methods from package that achieves interactive visualization</li>
</ul>
<p><br></p>
<div id="vitessce" class="section level2">
<h2>Vitessce</h2>
<p>We will transform VoltRon objects of Xenium data into zarr arrays,
and use them for interactive visualization in <a
href="http://vitessce.io/">Vitessce</a>. We should first download the
vitessceR package which incorporates wrapper function to visualize zarr
arrays interactively in R.</p>
<pre class="r watch-out"><code>if (!require("devtools", quietly = TRUE))
install.packages("devtools")
if (!require("vitessceR", quietly = TRUE))
devtools::install_github("Artur-man/vitessceR")</code></pre>
<p>We can convert the VoltRon object into an anndata object and save it
as a a zarr array using the <strong>as.AnnData</strong> function which
will create the array in the specified location. We use the
<strong>flip_coordinates=TRUE</strong> argument to flip the coordinates
of cells vertically, hence match it with the top to bottom system of the
background DAPI image. Also, we can save an OMETIFF file of the DAPI
image using <strong>create.ometiff</strong> arguement to be used by
vitessceR later.</p>
<pre class="r watch-out"><code>xenium_data <- as.AnnData(xenium_data, file = "xenium_data.zarr", assay = "Xenium",
flip_coordinates = TRUE, create.ometiff = TRUE)</code></pre>
<p><br></p>
<p>We can use the zarr file directly in the
<strong>vrSpatialPlot</strong> function to visualize the zarr array
interactively in Rstudio viewer. The <strong>reduction</strong>
arguement allows the umap of the Xenium data to be visualized alongside
with the spatial coordinates of the Xenium cells (thus associated cell
segmentations).</p>
<pre class="r watch-out"><code>vrSpatialPlot("xenium_data.zarr", group.by = "clusters", reduction = "umap")</code></pre>
<p><img width="90%" height="90%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/interactive_vitessce.png" class="center"></p>
<p><br></p>
<p>The vitessce application in the viewer pane allows visualizing
background DAPI image and segmentations simultaneously while allowing
users to zoom in and control the pane for advanced visualization.</p>
<p><img width="90%" height="90%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/interactive_vitessce_zoom.png" class="center"></p>
<p><br></p>
</div>
<div id="tissuumaps" class="section level2">
<h2>TissUUmaps</h2>
<p>To use <strong>TissUUmaps</strong> for interactive investigation of
your spatial omic data, we first need to convert the VoltRon object into
an anndata object. However, this time we save the anndata object as an
h5ad array using again the <strong>as.AnnData</strong> function which
will create the array in the specified location. We use the
<strong>flip_coordinates=TRUE</strong> argument to flip the coordinates
of cells vertically, hence match it with the top to bottom system of the
background DAPI image.</p>
<pre class="r watch-out"><code>as.AnnData(xenium_data, file = "xenium_data.h5ad", assay = "Xenium", flip_coordinates = TRUE)</code></pre>
<p>To use <strong>TissUUmaps</strong>, you can follow the instructions
<a href="https://tissuumaps.github.io/installation/">here</a>. Once
installed and executed, simply drag and drop the h5ad file to the main
panel of the application</p>
<p><img width="100%" height="100%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/interactive_tissuumaps.png" class="center"></p>
<p><br></p>
</div>
<div id="voltron" class="section level2">
<h2>VoltRon</h2>
<p>You can also use the built-in Shiny-based interactive visualizers of
the VoltRon package by calling <strong>interactive=TRUE</strong>. You
can zoom in by drawing a box on the plot and double-clicking in the
selected area.</p>
<pre class="r watch-out"><code>vrSpatialPlot(xenium_data, group.by = "clusters", plot.segments = TRUE, interactive = TRUE)</code></pre>
<p><img width="85%" height="85%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/interactive_voltron.png" class="center"></p>
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