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<h1 class="title toc-ignore">Molecule Analysis</h1>
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<p><br></p>
<div id="xenium-breast-cancer-data" class="section level1">
<h1>Xenium Breast Cancer Data</h1>
<p>VoltRon is an end-to-end spatial omic analysis package which also
supports investigating spatial points in sub-cellular resolution,
including those that are based on Fluorescence in situ hybrizrization
where one can spatially locate each individual molecule that are
hybridrized.</p>
<p>In this use case, we analyse readouts of the experiments conducted on
example tissue sections analysed by the <a
href="https://www.10xgenomics.com/platforms/xenium">Xenium In Situ</a>
platform. Two tissue sections of 5 <span
class="math inline">\(\mu\)</span>m tickness are derived from a single
formalin-fixed, paraffin-embedded (FFPE) breast cancer tissue block.
More information on the spatial datasets and the study can be also be
found on the <a
href="https://www.biorxiv.org/content/10.1101/2022.10.06.510405v1">BioArxiv
preprint</a>.</p>
<p>You can import these readouts from the <a
href="https://www.10xgenomics.com/products/xenium-in-situ/preview-dataset-human-breast">10x
Genomics website</a> (specifically, import <strong>In Situ Replicate
1/2</strong>). Alternatively, you can <strong>download a zipped
collection of Xenium readouts</strong> from <a
href="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/SpatialDataAlignment/Xenium_vs_Visium/10X_Xenium_Visium.zip">here</a>.</p>
<p><br></p>
<div id="building-voltron-objects" class="section level2">
<h2>Building VoltRon objects</h2>
<p>VoltRon includes built-in functions for converting readouts of Xenium
experiments into VoltRon objects. The <strong>importXenium</strong>
function locates all readout documents under the output folder of the
Xenium experiment, and forms a VoltRon object. In this case, the Xenium
data includes two assays (in the same layer) where one is the cell
segmentation based cell profile data and the other is the pure molecule
assay where the identity (gene of origin) of RNA molecules are
given.</p>
<pre class="r watch-out"><code>library(VoltRon)
Xen_R1 <- importXenium("Xenium_R1/outs", sample_name = "XeniumR1", import_molecules = TRUE)
Xen_R1</code></pre>
<pre><code>VoltRon Object
XeniumR1:
Layers: Section1
Assays: Xenium(Main) Xenium_mol </code></pre>
<p><br></p>
</div>
<div id="ondisk-support-optional" class="section level2">
<h2>Ondisk Support <strong>(Optional)</strong></h2>
<p>You can also save the imported VoltRon object to disk and still
accomplish analysis on molecule datasets.</p>
<pre class="r watch-out"><code>Xen_R1 <- saveVoltRon(Xen_R1, format = "HDF5VoltRon",
output = "Xen_R1/", replace = TRUE)</code></pre>
<p>The disk-backed data can be loaded once saved on disk again</p>
<pre class="r watch-out"><code>Xen_R1_disk <- loadVoltRon("Xen_R1/")</code></pre>
<p><br></p>
</div>
<div id="spatial-visualization" class="section level2">
<h2>Spatial Visualization</h2>
<p>With <strong>vrSpatialPlot</strong>, we can visualize Xenium
experiments in subcellular context. We first visualize mRNAs of ACTA2, a
marker for smooth muscle cell actin, and other markers found in the
breast cancer tissue sample. We can interactively select a subset of
interest within the tissue section and visualize the localization of
these transcripts. Here we subset a ductal carcinoma niche, and
visualize mRNAs of four genes.</p>
<pre class="r watch-out"><code>Xen_R1_subset <- subset(Xen_R1, interactive = TRUE)
Xen_R1_subset <- Xen_R1_subset$subsets[[1]]
vrSpatialPlot(Xen_R1_subset, assay = "Xenium_mol", group.by = "gene",
group.id = c("ACTA2", "KRT15", "TACSTD2", "CEACAM6"), pt.size = 0.2, legend.pt.size = 5)</code></pre>
<p><img width="70%" height="70%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/cellspot_transcripts_visualize.png" class="center"></p>
<p><br></p>
<p>We can use the <strong>n.tile</strong> argument to divide the count
of selected group.ids (e.g. genes here) into hexagonal bins. We will use
this argument to divide the x and y-axis into 100 tiles and aggregate
transcript counts from select <strong>group.id</strong></p>
<pre class="r watch-out"><code>vrSpatialPlot(Xen_R1_subset, assay = "Xenium_mol", group.by = "gene", group.id = "ACTA2",
legend.pt.size = 5, n.tile = 100, background.color = "black")</code></pre>
<p><img width="70%" height="70%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/cellspot_transcripts_visualize_bins.png" class="center"></p>
<p><br></p>
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