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<h1 class="title toc-ignore">Census Datasets example</h1>
<!--
THIS VIGNETTE IS BASED ON:
https://github.com/chanzuckerberg/cell-census/blob/main/api/python/notebooks/api_demo/census_datasets.ipynb
-->
<p><em>Goal:</em> demonstrate basic use of the
<code>census_datasets</code> data frame.</p>
<p>Each Cell Census contains a top-level data frame itemizing the
datasets contained therein. You can read this <code>SOMADataFrame</code>
into an <a href="https://arrow.apache.org/docs/r/reference/Table.html">Arrow
Table</a>:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>census <span class="ot">&lt;-</span> CellCensus<span class="sc">::</span><span class="fu">open_soma</span>()</span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>census_datasets <span class="ot">&lt;-</span> census<span class="sc">$</span><span class="fu">get</span>(<span class="st">&quot;census_info&quot;</span>)<span class="sc">$</span><span class="fu">get</span>(<span class="st">&quot;datasets&quot;</span>)<span class="sc">$</span><span class="fu">read</span>()</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(census_datasets)</span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Table</span></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; 503 rows x 8 columns</span></span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $soma_joinid &lt;int64 not null&gt;</span></span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $collection_id &lt;large_string not null&gt;</span></span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $collection_name &lt;large_string not null&gt;</span></span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $collection_doi &lt;large_string not null&gt;</span></span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $dataset_id &lt;large_string not null&gt;</span></span>
<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $dataset_title &lt;large_string not null&gt;</span></span>
<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $dataset_h5ad_path &lt;large_string not null&gt;</span></span>
<span id="cb1-13"><a href="#cb1-13" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $dataset_total_cell_count &lt;int64 not null&gt;</span></span></code></pre></div>
<p>and then an R data frame:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>census_datasets <span class="ot">&lt;-</span> <span class="fu">as.data.frame</span>(census_datasets)</span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(census_datasets[, <span class="fu">c</span>(</span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a> <span class="st">&quot;dataset_id&quot;</span>,</span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a> <span class="st">&quot;dataset_title&quot;</span>,</span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a> <span class="st">&quot;dataset_total_cell_count&quot;</span></span>
<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a>)], <span class="at">n =</span> <span class="dv">5</span>)</span>
<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; # A tibble: 503 × 3</span></span>
<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; dataset_id dataset_title dataset_total_cell_c…¹</span></span>
<span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; &lt;chr&gt; &lt;chr&gt; &lt;int&gt;</span></span>
<span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; 1 f512b8b6-369d-4a85-a695-116e0806857f Skin 68036</span></span>
<span id="cb2-11"><a href="#cb2-11" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; 2 90d4a63b-5c02-43eb-acde-c49345681601 Fallopian tube RNA 60574</span></span>
<span id="cb2-12"><a href="#cb2-12" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; 3 d1207c81-7309-43a7-a5a0-f4283670b62b Ovary RNA 26134</span></span>
<span id="cb2-13"><a href="#cb2-13" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; 4 58b01044-c5e5-4b0f-8a2d-6ebf951e01ff A scRNA-seq atlas… 130908</span></span>
<span id="cb2-14"><a href="#cb2-14" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; 5 97d9238c-1a39-4873-b0bb-963ec2d788e6 MSK SPECTRUM - De… 24025</span></span>
<span id="cb2-15"><a href="#cb2-15" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; # ℹ 498 more rows</span></span>
<span id="cb2-16"><a href="#cb2-16" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; # ℹ abbreviated name: ¹​dataset_total_cell_count</span></span></code></pre></div>
<p>The sum of cell counts across all datasets should match the number of
cells across all SOMA experiments (human, mouse).</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>census_data <span class="ot">&lt;-</span> census<span class="sc">$</span><span class="fu">get</span>(<span class="st">&quot;census_data&quot;</span>)</span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>all_experiments <span class="ot">&lt;-</span> <span class="fu">lapply</span>(census_data<span class="sc">$</span><span class="fu">to_list</span>(), <span class="cf">function</span>(it) census_data<span class="sc">$</span><span class="fu">get</span>(it<span class="sc">$</span>name))</span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(all_experiments)</span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $homo_sapiens</span></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; &lt;SOMAExperiment&gt;</span></span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; uri: s3://cellxgene-data-public/cell-census/2023-03-16/soma/census_data/homo_sapiens </span></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; arrays: obs* </span></span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; groups: ms* </span></span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
<span id="cb3-10"><a href="#cb3-10" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $mus_musculus</span></span>
<span id="cb3-11"><a href="#cb3-11" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; &lt;SOMAExperiment&gt;</span></span>
<span id="cb3-12"><a href="#cb3-12" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; uri: s3://cellxgene-data-public/cell-census/2023-03-16/soma/census_data/mus_musculus </span></span>
<span id="cb3-13"><a href="#cb3-13" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; arrays: obs* </span></span>
<span id="cb3-14"><a href="#cb3-14" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; groups: ms*</span></span></code></pre></div>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>experiments_total_cells <span class="ot">&lt;-</span> <span class="fu">sum</span>(<span class="fu">sapply</span>(all_experiments, <span class="cf">function</span>(it) {</span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">nrow</span>(it<span class="sc">$</span>obs<span class="sc">$</span><span class="fu">read</span>(<span class="at">column_names =</span> <span class="fu">c</span>(<span class="st">&quot;soma_joinid&quot;</span>)))</span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a>}))</span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(<span class="fu">paste</span>(<span class="st">&quot;Found&quot;</span>, experiments_total_cells, <span class="st">&quot;cells in all experiments.&quot;</span>))</span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; [1] &quot;Found 48311298 cells in all experiments.&quot;</span></span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(<span class="fu">paste</span>(</span>
<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a> <span class="st">&quot;Found&quot;</span>, <span class="fu">sum</span>(<span class="fu">as.vector</span>(census_datasets<span class="sc">$</span>dataset_total_cell_count)),</span>
<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a> <span class="st">&quot;cells in all datasets.&quot;</span></span>
<span id="cb4-9"><a href="#cb4-9" aria-hidden="true" tabindex="-1"></a>))</span>
<span id="cb4-10"><a href="#cb4-10" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; [1] &quot;Found 48311298 cells in all datasets.&quot;</span></span></code></pre></div>
<p>Let’s pick one dataset to slice out of the census, and turn into a
Seurat in-memory object. (This requires the <code>Seurat</code> package
to have been installed beforehand.)</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>census_datasets[census_datasets<span class="sc">$</span>dataset_id <span class="sc">==</span> <span class="st">&quot;0bd1a1de-3aee-40e0-b2ec-86c7a30c7149&quot;</span>, ]</span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; # A tibble: 1 × 8</span></span>
<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; soma_joinid collection_id collection_name collection_doi dataset_id</span></span>
<span id="cb5-4"><a href="#cb5-4" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; &lt;int&gt; &lt;chr&gt; &lt;chr&gt; &lt;chr&gt; &lt;chr&gt; </span></span>
<span id="cb5-5"><a href="#cb5-5" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; 1 345 0b9d8a04-bb9d-44da-aa27… Tabula Muris S… 10.1038/s4158… 0bd1a1de-…</span></span>
<span id="cb5-6"><a href="#cb5-6" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; # ℹ 3 more variables: dataset_title &lt;chr&gt;, dataset_h5ad_path &lt;chr&gt;,</span></span>
<span id="cb5-7"><a href="#cb5-7" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; # dataset_total_cell_count &lt;int&gt;</span></span></code></pre></div>
<p>Create a query on the mouse experiment, “RNA” measurement, for the
<code>dataset_id</code>.</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>obs_query <span class="ot">&lt;-</span> tiledbsoma<span class="sc">::</span>SOMAAxisQuery<span class="sc">$</span><span class="fu">new</span>(</span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a> <span class="at">value_filter =</span> <span class="st">&quot;dataset_id == &#39;0bd1a1de-3aee-40e0-b2ec-86c7a30c7149&#39;&quot;</span></span>
<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a>)</span>
<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a>expt_query <span class="ot">&lt;-</span> tiledbsoma<span class="sc">::</span>SOMAExperimentAxisQuery<span class="sc">$</span><span class="fu">new</span>(</span>
<span id="cb6-5"><a href="#cb6-5" aria-hidden="true" tabindex="-1"></a> census_data<span class="sc">$</span><span class="fu">get</span>(<span class="st">&quot;mus_musculus&quot;</span>), <span class="st">&quot;RNA&quot;</span>,</span>
<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a> <span class="at">obs_query =</span> obs_query</span>
<span id="cb6-7"><a href="#cb6-7" aria-hidden="true" tabindex="-1"></a>)</span>
<span id="cb6-8"><a href="#cb6-8" aria-hidden="true" tabindex="-1"></a>dataset_seurat <span class="ot">&lt;-</span> expt_query<span class="sc">$</span><span class="fu">to_seurat</span>(<span class="fu">c</span>(<span class="at">counts =</span> <span class="st">&quot;raw&quot;</span>))</span>
<span id="cb6-9"><a href="#cb6-9" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Warning: No reductions found</span></span>
<span id="cb6-10"><a href="#cb6-10" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Warning: No graphs found in &#39;obsp&#39;</span></span>
<span id="cb6-11"><a href="#cb6-11" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(dataset_seurat)</span>
<span id="cb6-12"><a href="#cb6-12" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; An object of class Seurat </span></span>
<span id="cb6-13"><a href="#cb6-13" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; 52392 features across 40220 samples within 1 assay </span></span>
<span id="cb6-14"><a href="#cb6-14" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Active assay: RNA (52392 features, 0 variable features)</span></span></code></pre></div>
<p>You can also use the <code>CellCensus::get_source_h5ad_uri()</code>
API to fetch a URI pointing to the H5AD associated with this dataset_id.
This is the same H5AD you can download from the CELLxGENE Portal, and
may contain additional data-submitter provided information which was not
included in the Cell Census.</p>
<p>The “locator” returned by this API will include a URI and additional
information that may be necessary to use the URI (eg, the S3
region).</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>CellCensus<span class="sc">::</span><span class="fu">get_source_h5ad_uri</span>(<span class="st">&quot;0bd1a1de-3aee-40e0-b2ec-86c7a30c7149&quot;</span>)</span>
<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $uri</span></span>
<span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; [1] &quot;s3://cellxgene-data-public/cell-census/2023-03-16/h5ads/0bd1a1de-3aee-40e0-b2ec-86c7a30c7149.h5ad&quot;</span></span>
<span id="cb7-4"><a href="#cb7-4" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; </span></span>
<span id="cb7-5"><a href="#cb7-5" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; $s3_region</span></span>
<span id="cb7-6"><a href="#cb7-6" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; [1] &quot;us-west-2&quot;</span></span></code></pre></div>
<p>The <code>CellCensus::download_source_h5ad()</code> API downloads the
H5AD to a local file, which can then be used in R using <a href="https://mojaveazure.github.io/seurat-disk/articles/convert-anndata.html">SeuratDisk’s
anndata converter</a>.</p>
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