Merge pull request #103 from AlexsLemonade/allyhawkins/missing-spaces

[ci skip]

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manuscript.html

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+  <link rel="alternate" type="text/html" href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/8558b4ff6642aea1bc281adf72273b014a0aae57/" />
+  <meta name="manubot_html_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/8558b4ff6642aea1bc281adf72273b014a0aae57/" />
+  <meta name="manubot_pdf_url_versioned" content="https://AlexsLemonade.github.io/ScPCA-manuscript/v/8558b4ff6642aea1bc281adf72273b014a0aae57/manuscript.pdf" />
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@@ -139,9 +139,9 @@ <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/397aa4e910534d767c484d41cf912135d82b9c80/">permalink</a>)
+(<a href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/8558b4ff6642aea1bc281adf72273b014a0aae57/">permalink</a>)
 was automatically generated
-from <a href="https://github.com/AlexsLemonade/ScPCA-manuscript/tree/397aa4e910534d767c484d41cf912135d82b9c80">AlexsLemonade/ScPCA-manuscript@397aa4e</a>
+from <a href="https://github.com/AlexsLemonade/ScPCA-manuscript/tree/8558b4ff6642aea1bc281adf72273b014a0aae57">AlexsLemonade/ScPCA-manuscript@8558b4f</a>
 on March 25, 2024.
 </em></small></p>
 <h2 id="authors">Authors</h2>
@@ -382,7 +382,7 @@ <h2 id="uniform-processing-of-data-available-on-the-scpca-portal">Uniform proces
 The unfiltered gene by cell counts matrices are filtered to remove any barcodes that are not likely to contain cells using <code>DropletUtils::emptyDropsCellRanger()</code><span class="citation" data-cites="U2Fa25dp">[<a href="#ref-U2Fa25dp" role="doc-biblioref">37</a>]</span>, and all cells that pass are saved in a <code>SingleCellExperiment</code> object and a file with the suffix <code>_filtered.rds</code>.
 Low-quality cells are identified and removed with <code>miQC</code> <span class="citation" data-cites="17Yhk1HAt">[<a href="#ref-17Yhk1HAt" role="doc-biblioref">38</a>]</span>, which jointly models the proportion of mitochondrial reads and detected genes per cell and calculates a probability that each cell is compromised.
 The remaining cells’ counts are normalized <span class="citation" data-cites="vpU0FTFY">[<a href="#ref-vpU0FTFY" role="doc-biblioref">39</a>]</span>, and reduced-dimension representations are calculated using both principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) <span class="citation" data-cites="157h5hA34">[<a href="#ref-157h5hA34" role="doc-biblioref">40</a>]</span>.
-Finally, cell types are classified using two automated methods, <code>SingleR</code><span class="citation" data-cites="13P6oSrS0">[<a href="#ref-13P6oSrS0" role="doc-biblioref">41</a>]</span> and <code>CellAssign</code><span class="citation" data-cites="HES0WO6k">[<a href="#ref-HES0WO6k" role="doc-biblioref">42</a>]</span>.
+Finally, cell types are classified using two automated methods, <code>SingleR</code> <span class="citation" data-cites="13P6oSrS0">[<a href="#ref-13P6oSrS0" role="doc-biblioref">41</a>]</span> and <code>CellAssign</code> <span class="citation" data-cites="HES0WO6k">[<a href="#ref-HES0WO6k" role="doc-biblioref">42</a>]</span>.
 The results from this analysis are stored in a processed <code>SingleCellExperiment</code> object saved to a file with the suffix <code>_processed.rds</code>.</p>
 <p>To make downloading from the Portal convenient for R and Python users, downloads are available as either <code>SingleCellExperiment</code> or <code>AnnData</code><span class="citation" data-cites="KRBW8xeZ">[<a href="#ref-KRBW8xeZ" role="doc-biblioref">43</a>]</span> objects.
 <code>scpca-nf</code> converts all <code>SingleCellExperiment</code> objects to <code>AnnData</code> objects, which are saved as <code>.hdf5</code> files (Figure <a href="#fig:fig2">2</a>A).

manuscript.md

@@ -38,8 +38,8 @@ header-includes: |
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   <meta name="citation_publication_date" content="2024-03-25" />
   <meta property="article:published_time" content="2024-03-25" />
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-  <meta property="article:modified_time" content="2024-03-25T15:56:18+00:00" />
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@@ -93,9 +93,9 @@ header-includes: |
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+  <link rel="alternate" type="text/html" href="https://AlexsLemonade.github.io/ScPCA-manuscript/v/8558b4ff6642aea1bc281adf72273b014a0aae57/" />
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@@ -117,9 +117,9 @@ manubot-clear-requests-cache: false
 
 <small><em>
 This manuscript
-([permalink](https://AlexsLemonade.github.io/ScPCA-manuscript/v/397aa4e910534d767c484d41cf912135d82b9c80/))
+([permalink](https://AlexsLemonade.github.io/ScPCA-manuscript/v/8558b4ff6642aea1bc281adf72273b014a0aae57/))
 was automatically generated
-from [AlexsLemonade/ScPCA-manuscript@397aa4e](https://github.com/AlexsLemonade/ScPCA-manuscript/tree/397aa4e910534d767c484d41cf912135d82b9c80)
+from [AlexsLemonade/ScPCA-manuscript@8558b4f](https://github.com/AlexsLemonade/ScPCA-manuscript/tree/8558b4ff6642aea1bc281adf72273b014a0aae57)
 on March 25, 2024.
 </em></small>
 
@@ -406,7 +406,7 @@ This unfiltered counts matrix is stored in a `SingleCellExperiment` object [@doi
 The unfiltered gene by cell counts matrices are filtered to remove any barcodes that are not likely to contain cells using `DropletUtils::emptyDropsCellRanger()`[@doi:10.1186/s13059-019-1662-y], and all cells that pass are saved in a `SingleCellExperiment` object and a file with the suffix `_filtered.rds`.
 Low-quality cells are identified and removed with `miQC` [@doi:10.1371/journal.pcbi.1009290], which jointly models the proportion of mitochondrial reads and detected genes per cell and calculates a probability that each cell is compromised.
 The remaining cells' counts are normalized [@doi:10.1186/s13059-016-0947-7], and reduced-dimension representations are calculated using both principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) [@arxiv:1802.03426].
-Finally, cell types are classified using two automated methods, `SingleR`[@doi:10.1038/s41590-018-0276-y] and `CellAssign`[@doi:10.1038/s41592-019-0529-1].
+Finally, cell types are classified using two automated methods, `SingleR` [@doi:10.1038/s41590-018-0276-y] and `CellAssign` [@doi:10.1038/s41592-019-0529-1].
 The results from this analysis are stored in a processed `SingleCellExperiment` object saved to a file with the suffix `_processed.rds`.
 
 To make downloading from the Portal convenient for R and Python users, downloads are available as either `SingleCellExperiment` or `AnnData`[@doi:10.1101/2021.12.16.473007] objects.

spelling-errors.txt

@@ -35,7 +35,7 @@ SJS
 sjspielman
 SMF
 Spielman
-taroni
+Taroni
 TODO
 UTHealth
 Venkatesh