Merge pull request #233 from AlexsLemonade/sjspielman/215-cell-type-discussion

[ci skip]

This build is based on
fae3f10.

This commit was created by the following CI build and job:
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Author: sjspielman

README.md

@@ -1,7 +1,7 @@
 # Output directory containing the formatted manuscript
 
 The [`gh-pages`](https://github.com/AlexsLemonade/ScPCA-manuscript/tree/gh-pages) branch hosts the contents of this directory at <https://AlexsLemonade.github.io/ScPCA-manuscript/>.
-The permalink for this webpage version is <https://AlexsLemonade.github.io/ScPCA-manuscript/v/d1a3a258870f80ad61148e0bfb7d0ceff3658437/>.
+The permalink for this webpage version is <https://AlexsLemonade.github.io/ScPCA-manuscript/v/fae3f10ff241bf5530095c5a43b91723fd7756bc/>.
 To redirect to the permalink for the latest manuscript version at anytime, use the link <https://AlexsLemonade.github.io/ScPCA-manuscript/v/freeze/>.
 
 ## Files
@@ -35,4 +35,4 @@ Verifying timestamps with the `ots verify` command requires running a local bitc
 ## Source
 
 The manuscripts in this directory were built from
-[`d1a3a258870f80ad61148e0bfb7d0ceff3658437`](https://github.com/AlexsLemonade/ScPCA-manuscript/commit/d1a3a258870f80ad61148e0bfb7d0ceff3658437).
+[`fae3f10ff241bf5530095c5a43b91723fd7756bc`](https://github.com/AlexsLemonade/ScPCA-manuscript/commit/fae3f10ff241bf5530095c5a43b91723fd7756bc).

index.html

@@ -66,8 +66,8 @@
   <meta name="dc.date" content="2026-01-12" />
   <meta name="citation_publication_date" content="2026-01-12" />
   <meta property="article:published_time" content="2026-01-12" />
-  <meta name="dc.modified" content="2026-01-12T17:36:06+00:00" />
-  <meta property="article:modified_time" content="2026-01-12T17:36:06+00:00" />
+  <meta name="dc.modified" content="2026-01-12T17:59:23+00:00" />
+  <meta property="article:modified_time" content="2026-01-12T17:59:23+00:00" />
   <meta name="dc.language" content="en-US" />
   <meta name="citation_language" content="en-US" />
   <meta name="dc.relation.ispartof" content="Manubot" />
@@ -121,9 +121,9 @@
   <meta name="citation_fulltext_html_url" content="https://AlexsLemonade.github.io/ScPCA-manuscript/" />
   <meta name="citation_pdf_url" content="https://AlexsLemonade.github.io/ScPCA-manuscript/manuscript.pdf" />
   <link rel="alternate" type="application/pdf" href="https://AlexsLemonade.github.io/ScPCA-manuscript/manuscript.pdf" />
-  <link rel="alternate" type="text/html" href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/d1a3a258870f80ad61148e0bfb7d0ceff3658437/" />
-  <meta name="manubot_html_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/d1a3a258870f80ad61148e0bfb7d0ceff3658437/" />
-  <meta name="manubot_pdf_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/d1a3a258870f80ad61148e0bfb7d0ceff3658437/manuscript.pdf" />
+  <link rel="alternate" type="text/html" href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/fae3f10ff241bf5530095c5a43b91723fd7756bc/" />
+  <meta name="manubot_html_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/fae3f10ff241bf5530095c5a43b91723fd7756bc/" />
+  <meta name="manubot_pdf_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/fae3f10ff241bf5530095c5a43b91723fd7756bc/manuscript.pdf" />
   <meta property="og:type" content="article" />
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   <link rel="icon" type="image/png" sizes="192x192" href="https://manubot.org/favicon-192x192.png" />
@@ -140,9 +140,9 @@ <h1 class="title">The Single-cell Pediatric Cancer Atlas: Data portal and open-s
 </header>
 <p><small><em>
 This manuscript
-(<a href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/d1a3a258870f80ad61148e0bfb7d0ceff3658437/">permalink</a>)
+(<a href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/fae3f10ff241bf5530095c5a43b91723fd7756bc/">permalink</a>)
 was automatically generated
-from <a href="https://github.com/AlexsLemonade/ScPCA-manuscript/tree/d1a3a258870f80ad61148e0bfb7d0ceff3658437">AlexsLemonade/ScPCA-manuscript@d1a3a25</a>
+from <a href="https://github.com/AlexsLemonade/ScPCA-manuscript/tree/fae3f10ff241bf5530095c5a43b91723fd7756bc">AlexsLemonade/ScPCA-manuscript@fae3f10</a>
 on January 12, 2026.
 </em></small></p>
 <h2 id="authors">Authors</h2>
@@ -762,10 +762,15 @@ <h2 id="discussion">Discussion</h2>
 Providing data as <code>AnnData</code> objects also means users can easily integrate ScPCA data with data and tools available on other platforms.
 In particular, the format of the provided <code>AnnData</code> objects was designed to be mostly compliant with the requirements of CZI CELLxGENE <span class="citation" data-cites="115InIIhW WrWip7GV 7NobF7Ei">[<a href="#ref-115InIIhW" role="doc-biblioref">5</a>,<a href="#ref-WrWip7GV" role="doc-biblioref">6</a>,<a href="#ref-7NobF7Ei" role="doc-biblioref">89</a>]</span>, but these objects can also be used with UCSC Cell Browser <span class="citation" data-cites="xCP3BjTw VKaQa2Z3">[<a href="#ref-xCP3BjTw" role="doc-biblioref">90</a>,<a href="#ref-VKaQa2Z3" role="doc-biblioref">91</a>]</span> or Kana <span class="citation" data-cites="1DswCJYT0 1FzXrvESX">[<a href="#ref-1DswCJYT0" role="doc-biblioref">92</a>,<a href="#ref-1FzXrvESX" role="doc-biblioref">93</a>]</span>.
 Additionally, users can download a merged <code>SingleCellExperiment</code> or <code>AnnData</code> object containing all gene expression data and metadata from all samples in a project, which supports multi-sample analyses such as differential gene expression or gene set enrichment.</p>
-<p>To provide users with cell type annotations, we used two automated methods, <code>SingleR</code> and <code>CellAssign</code>, which use publicly available references.
-We then used the correspondence between methods to derive ontology-aware consensus cell type labels.
-A limitation of our annotation approach is that the references we used do not contain tumor cells; therefore, tumor cells are likely poorly assigned.
-However, the consensus cell type labels provide a consistent labeling scheme across samples and may be beneficial for annotating populations of normal cells that may be present in tumor samples.</p>
+<p>To provide users with cell type annotations, we used three automated methods: <code>SingleR</code>, <code>CellAssign</code>, and <code>SCimilarity</code>.
+The first two approaches use publicly available references, while the third uses a foundation model to label cells.
+We then used the correspondence among these three methods to derive ontology-aware consensus cell type labels, thereby providing a consistent labeling scheme across samples that may support annotating populations of normal cells that may be present in tumor samples.
+A limitation of this approach is that neither of the references used for <code>SingleR</code> or <code>CellAssign</code> considered tumor cells; therefore, tumor cells are likely poorly assigned.
+To help circumvent this limitation, we have additionally provided CNV estimates, as inferred with <code>InferCNV</code>, for the majority of libraries in the Portal.
+Joint information from consensus cell type annotations and CNV estimates may support researchers to identify and interrogate tumor cells, in particular for diagnoses where copy number alterations are common such as neuroblastoma (Figure ??) or osteosarcoma.</p>
+<p>Beyond the automated and consensus cell type annotations, two projects (<code>SCPCP000004</code> comprised of neuroblastoma samples, and <code>SCPCP000015</code> comprised of Ewing sarcoma samples) include an additional set of cell type annotations from the ongoing OpenScPCA project <span class="citation" data-cites="xW9vfui5">[<a href="#ref-xW9vfui5" role="doc-biblioref">80</a>]</span>.
+Unlike annotations made within the <code>scpca-nf</code> pipeline, these labels do include formal identification of normal vs. tumor cells.
+Moving forward, we will continue to expand the set of projects on the Portal with OpenScPCA cell type annotations, thereby enriching the Portal with high-quality, well-documented annotations that support scientific discovery and reuse by the research community.</p>
 <p>Many samples on the Portal have additional sequencing data, including corresponding ADT data from CITE-seq, cell hashing data, bulk RNA-seq, or spatial transcriptomics.
 This enables users to gather more information about a single sample than they could from single-cell/nuclei RNA-seq alone.
 Samples with CITE-seq have additional information about cell-surface protein expression in individual cells, which can help determine cell types and correlate RNA to protein expression <span class="citation" data-cites="abp5rbw2">[<a href="#ref-abp5rbw2" role="doc-biblioref">34</a>]</span>.
@@ -1441,7 +1446,7 @@ <h2 class="page_break_before" id="references">References</h2>
 <div class="csl-left-margin">92. </div><div class="csl-right-inline"><strong>Powering single-cell analyses in the browser with WebAssembly</strong> <div class="csl-block">Aaron Lun, Jayaram Kancherla</div> <em>Cold Spring Harbor Laboratory</em> (2022-03-04) <a href="https://doi.org/gtk3dc">https://doi.org/gtk3dc</a> <div class="csl-block">DOI: <a href="https://doi.org/10.1101/2022.03.02.482701">10.1101/2022.03.02.482701</a></div></div>
 </div>
 <div id="ref-1FzXrvESX" class="csl-entry" role="doc-biblioentry">
-<div class="csl-left-margin">93. </div><div class="csl-right-inline"><strong>kana</strong> <a href="https://www.kanaverse.org/kana/">https://www.kanaverse.org/kana/</a></div>
+<div class="csl-left-margin">93. </div><div class="csl-right-inline"><a href="https://www.kanaverse.org/kana/">https://www.kanaverse.org/kana/</a></div>
 </div>
 <div id="ref-Whp3r83M" class="csl-entry" role="doc-biblioentry">
 <div class="csl-left-margin">94. </div><div class="csl-right-inline"><strong>A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics</strong> <div class="csl-block">Haoyang Li, Juexiao Zhou, Zhongxiao Li, Siyuan Chen, Xingyu Liao, Bin Zhang, Ruochi Zhang, Yu Wang, Shiwei Sun, Xin Gao</div> <em>Nature Communications</em> (2023-03-21) <a href="https://doi.org/gtk3c9">https://doi.org/gtk3c9</a> <div class="csl-block">DOI: <a href="https://doi.org/10.1038/s41467-023-37168-7">10.1038/s41467-023-37168-7</a> · PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36941264">36941264</a> · PMCID: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10027878">PMC10027878</a></div></div>