Merge pull request #114 from AlexsLemonade/allyhawkins/reorder-discus…

…sion

[ci skip]

This build is based on
c7ff2f0.

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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/3e6f15f202f1d13fc22bad98cc7ae12122f35339/>.
+The permalink for this webpage version is <https://AlexsLemonade.github.io/ScPCA-manuscript/v/c7ff2f075298dca1f9fb1ad25c579add373199a9/>.
 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
-[`3e6f15f202f1d13fc22bad98cc7ae12122f35339`](https://github.com/AlexsLemonade/ScPCA-manuscript/commit/3e6f15f202f1d13fc22bad98cc7ae12122f35339).
+[`c7ff2f075298dca1f9fb1ad25c579add373199a9`](https://github.com/AlexsLemonade/ScPCA-manuscript/commit/c7ff2f075298dca1f9fb1ad25c579add373199a9).

index.html

@@ -65,8 +65,8 @@
   <meta name="dc.date" content="2024-04-04" />
   <meta name="citation_publication_date" content="2024-04-04" />
   <meta property="article:published_time" content="2024-04-04" />
-  <meta name="dc.modified" content="2024-04-04T14:02:26+00:00" />
-  <meta property="article:modified_time" content="2024-04-04T14:02:26+00:00" />
+  <meta name="dc.modified" content="2024-04-04T15:28:02+00:00" />
+  <meta property="article:modified_time" content="2024-04-04T15:28:02+00:00" />
   <meta name="dc.language" content="en-US" />
   <meta name="citation_language" content="en-US" />
   <meta name="dc.relation.ispartof" content="Manubot" />
@@ -118,9 +118,9 @@
   <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/3e6f15f202f1d13fc22bad98cc7ae12122f35339/" />
-  <meta name="manubot_html_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/3e6f15f202f1d13fc22bad98cc7ae12122f35339/" />
-  <meta name="manubot_pdf_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/3e6f15f202f1d13fc22bad98cc7ae12122f35339/manuscript.pdf" />
+  <link rel="alternate" type="text/html" href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/c7ff2f075298dca1f9fb1ad25c579add373199a9/" />
+  <meta name="manubot_html_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/c7ff2f075298dca1f9fb1ad25c579add373199a9/" />
+  <meta name="manubot_pdf_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/c7ff2f075298dca1f9fb1ad25c579add373199a9/manuscript.pdf" />
   <meta property="og:type" content="article" />
   <meta property="twitter:card" content="summary_large_image" />
   <link rel="icon" type="image/png" sizes="192x192" href="https://manubot.org/favicon-192x192.png" />
@@ -137,9 +137,9 @@ <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/3e6f15f202f1d13fc22bad98cc7ae12122f35339/">permalink</a>)
+(<a href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/c7ff2f075298dca1f9fb1ad25c579add373199a9/">permalink</a>)
 was automatically generated
-from <a href="https://github.com/AlexsLemonade/ScPCA-manuscript/tree/3e6f15f202f1d13fc22bad98cc7ae12122f35339">AlexsLemonade/ScPCA-manuscript@3e6f15f</a>
+from <a href="https://github.com/AlexsLemonade/ScPCA-manuscript/tree/c7ff2f075298dca1f9fb1ad25c579add373199a9">AlexsLemonade/ScPCA-manuscript@c7ff2f0</a>
 on April 4, 2024.
 </em></small></p>
 <h2 id="authors">Authors</h2>
@@ -705,17 +705,19 @@ <h2 id="discussion">Discussion</h2>
 <p>To provide users with cell type annotations, we used two automated methods, <code>SingleR</code> and <code>CellAssign</code>, which use public references.
 As the publicly available references we used do not contain tumor cells but only normal cells, we recognize that the annotations we provide are limited.
 Despite these limitations, these methods can provide a good starting point for users, particularly in helping to annotate populations of normal cells that may be present, as normal cells are represented in the reference.</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, enabling users to gather more information about a single sample than they could from single-cell or single-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">32</a>]</span>.
-Spatial transcriptomics data on the Portal are not single-cell resolution, making it hard to identify cell types and spatial patterns from the spatial data alone.
-By providing matching single-cell RNA-seq, users can implement analysis tools, like those that use single-cell RNA-seq to deconvolute spatial data, to gain more insights about the spatial data <span class="citation" data-cites="Whp3r83M">[<a href="#ref-Whp3r83M" role="doc-biblioref">70</a>]</span>.
-<!--TODO: Maybe find a specific reference or review about using bulk with single-cell? -->
-Similarly, users can gain more insight from bulk RNA-seq data available on the Portal by integrating with single-cell RNA-seq data from the same sample <span class="citation" data-cites="mgOojr60 GpuiAcfU">[<a href="#ref-mgOojr60" role="doc-biblioref">71</a>,<a href="#ref-GpuiAcfU" role="doc-biblioref">72</a>]</span>.</p>
 <p>We also introduced our open-source and efficient workflow for uniformly processing datasets available on the Portal, <code>scpca-nf</code>, which is available to the entire research community.
 In one command, <code>scpca-nf</code> can process raw data from various sequencing types, turning FASTQ files into processed <code>SingleCellExperiment</code> or <code>AnnData</code> objects ready for downstream analyses.
 Using Nextflow as the framework for <code>scpca-nf</code> means the workflow is both modular and portable.
 This makes it easy to add support for more modalities in the future, such as single-cell ATAC-seq, and allows others to run the workflow on their samples in their computing environment, maintaining the security of protected raw data.
-Processed output from running <code>scpca-nf</code> on samples from pediatric tumors, cell lines, or other model organisms is eligible for submission to the ScPCA Portal, enabling us to continue increasing the number of available samples freely available to all researchers.</p>
+Processed output from running <code>scpca-nf</code> on samples from pediatric tumors, cell lines, or other model organisms is eligible for submission to the ScPCA Portal, enabling us to continue increasing the number of samples available to researchers.</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, enabling users to gather more information about a single sample than they could from single-cell or single-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">32</a>]</span>.
+Spatial transcriptomics data on the Portal are not single-cell resolution, making it hard to identify cell types and spatial patterns from the spatial data alone.
+By providing matching single-cell RNA-seq, users can implement analysis tools, like those that use single-cell RNA-seq to deconvolute spatial data, to gain more insights about the spatial data <span class="citation" data-cites="Whp3r83M">[<a href="#ref-Whp3r83M" role="doc-biblioref">70</a>]</span>.
+Similarly, users can gain more insight from bulk RNA-seq data available on the Portal by integrating with single-cell RNA-seq data from the same sample <span class="citation" data-cites="mgOojr60 GpuiAcfU">[<a href="#ref-mgOojr60" role="doc-biblioref">71</a>,<a href="#ref-GpuiAcfU" role="doc-biblioref">72</a>]</span>.
+The single-cell RNA-seq data available on the Portal can also be used to deconvolute existing bulk RNA-seq datasets, allowing researchers to infer abundance of different cell types or cell states in bulk RNA-seq data.
+Data available on the ScPCA Portal can be used to re-analyze any existing pediatric cancer datasets with bulk RNA-seq, such as the Pediatric Brain Tumor Atlas <span class="citation" data-cites="U5WisTG5 5VXMHJ7N">[<a href="#ref-U5WisTG5" role="doc-biblioref">73</a>,<a href="#ref-5VXMHJ7N" role="doc-biblioref">74</a>]</span>.
+This allows researchers to glean more insight from previously published data without obtaining fresh samples, saving time and money.</p>
 <h2 id="acknowledgments">Acknowledgments</h2>
 <p>We thank the data generators and submitters of the Single-cell Pediatric Cancer Atlas.
 We also thank Anna Greene for her role in constructing the Single-cell Pediatric Cancer Atlas funding opportunity.</p>
@@ -1244,6 +1246,12 @@ <h2 class="page_break_before" id="references">References</h2>
 <div id="ref-GpuiAcfU" class="csl-entry" role="doc-biblioentry">
 <div class="csl-left-margin">72. </div><div class="csl-right-inline"><strong>Effective methods for bulk RNA-seq deconvolution using scnRNA-seq transcriptomes</strong> <div class="csl-block">Francisco Avila Cobos, Mohammad Javad Najaf Panah, Jessica Epps, Xiaochen Long, Tsz-Kwong Man, Hua-Sheng Chiu, Elad Chomsky, Evgeny Kiner, Michael J Krueger, Diego di Bernardo, … Pavel Sumazin</div> <em>Genome Biology</em> (2023-08-01) <a href="https://doi.org/gsmvqq">https://doi.org/gsmvqq</a> <div class="csl-block">DOI: <a href="https://doi.org/10.1186/s13059-023-03016-6">10.1186/s13059-023-03016-6</a> · PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/37528411">37528411</a> · PMCID: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10394903">PMC10394903</a></div></div>
 </div>
+<div id="ref-U5WisTG5" class="csl-entry" role="doc-biblioentry">
+<div class="csl-left-margin">73. </div><div class="csl-right-inline"><strong>The children's brain tumor network (CBTN) - Accelerating research in pediatric central nervous system tumors through collaboration and open science</strong> <div class="csl-block">Jena V Lilly, Jo Lynne Rokita, Jennifer L Mason, Tatiana Patton, Stephanie Stefankiewiz, David Higgins, Gerri Trooskin, Carina A Larouci, Kamnaa Arya, Elizabeth Appert, … Angela J Waanders</div> <em>Neoplasia</em> (2023-01) <a href="https://doi.org/grkvcf">https://doi.org/grkvcf</a> <div class="csl-block">DOI: <a href="https://doi.org/10.1016/j.neo.2022.100846">10.1016/j.neo.2022.100846</a> · PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36335802">36335802</a> · PMCID: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641002">PMC9641002</a></div></div>
+</div>
+<div id="ref-5VXMHJ7N" class="csl-entry" role="doc-biblioentry">
+<div class="csl-left-margin">74. </div><div class="csl-right-inline"><strong>OpenPBTA: The Open Pediatric Brain Tumor Atlas</strong> <div class="csl-block">Joshua A Shapiro, Krutika S Gaonkar, Stephanie J Spielman, Candace L Savonen, Chante J Bethell, Run Jin, Komal S Rathi, Yuankun Zhu, Laura E Egolf, Bailey K Farrow, … Jaclyn N Taroni</div> <em>Cell Genomics</em> (2023-07) <a href="https://doi.org/gr92p6">https://doi.org/gr92p6</a> <div class="csl-block">DOI: <a href="https://doi.org/10.1016/j.xgen.2023.100340">10.1016/j.xgen.2023.100340</a> · PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/37492101">37492101</a> · PMCID: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10363844">PMC10363844</a></div></div>
+</div>
 </div>
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