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diff --git a/.nojekyll b/.nojekyll
@@ -1 +1 @@
-9966aebb
+66fa5cf9
diff --git a/index.html b/index.html
@@ -117,7 +117,6 @@ <h2 id="toc-title">On this page</h2>
   <li><a href="#learning-objectives" id="toc-learning-objectives" class="nav-link" data-scroll-target="#learning-objectives">Learning objectives</a></li>
   <li><a href="#workshop-organisers" id="toc-workshop-organisers" class="nav-link" data-scroll-target="#workshop-organisers">Workshop organisers</a></li>
   <li><a href="#schedule" id="toc-schedule" class="nav-link" data-scroll-target="#schedule">Schedule</a></li>
-  <li><a href="#additional-materials" id="toc-additional-materials" class="nav-link" data-scroll-target="#additional-materials">Additional materials</a></li>
   </ul>
 </nav>
     </div>
@@ -146,6 +145,13 @@ <h2 class="anchored" data-anchor-id="welcome">Welcome</h2>
 <p>In this workshop we will introduce two R packages we developed for the analysis and simulation of spatial proteomics data (multiplex immunohistochemistry, CODEX, MIBI, IMC, etc) published this year in Nature Communications (Feng et al.&nbsp;2023). SPIAT (SPatial Image Analysis of Tissues) is a spatial-platform agnostic toolkit with a suite of spatial analysis algorithms, and spaSim (spatial Simulator) is a novel simulator of tissue spatial patterns.</p>
 <p>The workshop is designed for those who would like to get started with or improve their capacity to perform spatial data analyses. We will cover how to handle spatial proteomics data, from reading, formatting, and extensive spatial analysis through SPIAT’s six analysis modules. These range from quality control and visualisation to more advanced topics such as cell colocalisation, spatial heterogeneity, tumour structure characterisation, and neighbourhood identification.</p>
 <p>During the workshop, you will get an overview of the analysis workflow and understand the rationale behind specific functions. You will get your hands dirty by designing an analysis workflow using a real example dataset, so you’ll learn by doing.</p>
+<p>Please have a read of our recent paper (Nature Communications) if you are interested! <a href="https://www.nature.com/articles/s41467-023-37822-0">https://www.nature.com/articles/s41467-023-37822-0</a></p>
+<p>Links to the two packages:</p>
+<ul>
+<li><p><a href="https://github.com/TrigosTeam/SPIAT">SPIAT Github</a> and <a href="https://bioconductor.org/packages/release/bioc/html/SPIAT.html">SPIAT Bioconductor</a></p></li>
+<li><p><a href="https://github.com/TrigosTeam/spaSim">spaSim Github</a> and <a href="https://bioconductor.org/packages/release/bioc/html/spaSim.html">spaSim Bioconductor</a></p></li>
+</ul>
+<p>These two R packages were developed in the <a href="https://www.petermac.org/research/research-programs-and-labs/computational-biology-program/anna-trigos-lab">Anna Trigos Lab</a>.</p>
 </section>
 <section id="time-and-location" class="level2">
 <h2 class="anchored" data-anchor-id="time-and-location">Time and Location</h2>
@@ -255,16 +261,6 @@ <h2 class="anchored" data-anchor-id="schedule">Schedule</h2>
 </tr>
 </tbody>
 </table>
-</section>
-<section id="additional-materials" class="level2">
-<h2 class="anchored" data-anchor-id="additional-materials">Additional materials</h2>
-<p>Please have a read of our recent <a href="https://www.nature.com/articles/s41467-023-37822-0">paper</a> if you are interested!</p>
-<p>Links to the two packages:</p>
-<ul>
-<li><p><a href="https://github.com/TrigosTeam/SPIAT">SPIAT Github</a> and <a href="https://bioconductor.org/packages/release/bioc/html/SPIAT.html">SPIAT Bioconductor</a></p></li>
-<li><p><a href="https://github.com/TrigosTeam/spaSim">spaSim Github</a> and <a href="https://bioconductor.org/packages/release/bioc/html/spaSim.html">spaSim Bioconductor</a></p></li>
-</ul>
-<p>These two R packages were developed in the <a href="https://www.petermac.org/research/research-programs-and-labs/computational-biology-program/anna-trigos-lab">Anna Trigos Lab</a>.</p>
 
 
 </section>

diff --git a/search.json b/search.json
@@ -11,14 +11,14 @@
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-    "text": "In this workshop we will introduce two R packages we developed for the analysis and simulation of spatial proteomics data (multiplex immunohistochemistry, CODEX, MIBI, IMC, etc) published this year in Nature Communications (Feng et al. 2023). SPIAT (SPatial Image Analysis of Tissues) is a spatial-platform agnostic toolkit with a suite of spatial analysis algorithms, and spaSim (spatial Simulator) is a novel simulator of tissue spatial patterns.\nThe workshop is designed for those who would like to get started with or improve their capacity to perform spatial data analyses. We will cover how to handle spatial proteomics data, from reading, formatting, and extensive spatial analysis through SPIAT’s six analysis modules. These range from quality control and visualisation to more advanced topics such as cell colocalisation, spatial heterogeneity, tumour structure characterisation, and neighbourhood identification.\nDuring the workshop, you will get an overview of the analysis workflow and understand the rationale behind specific functions. You will get your hands dirty by designing an analysis workflow using a real example dataset, so you’ll learn by doing."
+    "text": "In this workshop we will introduce two R packages we developed for the analysis and simulation of spatial proteomics data (multiplex immunohistochemistry, CODEX, MIBI, IMC, etc) published this year in Nature Communications (Feng et al. 2023). SPIAT (SPatial Image Analysis of Tissues) is a spatial-platform agnostic toolkit with a suite of spatial analysis algorithms, and spaSim (spatial Simulator) is a novel simulator of tissue spatial patterns.\nThe workshop is designed for those who would like to get started with or improve their capacity to perform spatial data analyses. We will cover how to handle spatial proteomics data, from reading, formatting, and extensive spatial analysis through SPIAT’s six analysis modules. These range from quality control and visualisation to more advanced topics such as cell colocalisation, spatial heterogeneity, tumour structure characterisation, and neighbourhood identification.\nDuring the workshop, you will get an overview of the analysis workflow and understand the rationale behind specific functions. You will get your hands dirty by designing an analysis workflow using a real example dataset, so you’ll learn by doing.\nPlease have a read of our recent paper (Nature Communications) if you are interested! https://www.nature.com/articles/s41467-023-37822-0\nLinks to the two packages:\n\nSPIAT Github and SPIAT Bioconductor\nspaSim Github and spaSim Bioconductor\n\nThese two R packages were developed in the Anna Trigos Lab."
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-    "text": "In this workshop we will introduce two R packages we developed for the analysis and simulation of spatial proteomics data (multiplex immunohistochemistry, CODEX, MIBI, IMC, etc) published this year in Nature Communications (Feng et al. 2023). SPIAT (SPatial Image Analysis of Tissues) is a spatial-platform agnostic toolkit with a suite of spatial analysis algorithms, and spaSim (spatial Simulator) is a novel simulator of tissue spatial patterns.\nThe workshop is designed for those who would like to get started with or improve their capacity to perform spatial data analyses. We will cover how to handle spatial proteomics data, from reading, formatting, and extensive spatial analysis through SPIAT’s six analysis modules. These range from quality control and visualisation to more advanced topics such as cell colocalisation, spatial heterogeneity, tumour structure characterisation, and neighbourhood identification.\nDuring the workshop, you will get an overview of the analysis workflow and understand the rationale behind specific functions. You will get your hands dirty by designing an analysis workflow using a real example dataset, so you’ll learn by doing."
+    "text": "In this workshop we will introduce two R packages we developed for the analysis and simulation of spatial proteomics data (multiplex immunohistochemistry, CODEX, MIBI, IMC, etc) published this year in Nature Communications (Feng et al. 2023). SPIAT (SPatial Image Analysis of Tissues) is a spatial-platform agnostic toolkit with a suite of spatial analysis algorithms, and spaSim (spatial Simulator) is a novel simulator of tissue spatial patterns.\nThe workshop is designed for those who would like to get started with or improve their capacity to perform spatial data analyses. We will cover how to handle spatial proteomics data, from reading, formatting, and extensive spatial analysis through SPIAT’s six analysis modules. These range from quality control and visualisation to more advanced topics such as cell colocalisation, spatial heterogeneity, tumour structure characterisation, and neighbourhood identification.\nDuring the workshop, you will get an overview of the analysis workflow and understand the rationale behind specific functions. You will get your hands dirty by designing an analysis workflow using a real example dataset, so you’ll learn by doing.\nPlease have a read of our recent paper (Nature Communications) if you are interested! https://www.nature.com/articles/s41467-023-37822-0\nLinks to the two packages:\n\nSPIAT Github and SPIAT Bioconductor\nspaSim Github and spaSim Bioconductor\n\nThese two R packages were developed in the Anna Trigos Lab."
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@@ -75,12 +75,5 @@
     "title": "Overview of the workshop",
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     "text": "Schedule\n\n\n\nContent\nTime\n\n\n\n\nSetup\nPrior to workshop\n\n\nSession kick off\n9:00 - 9:10\n\n\nIntroduction to SPIAT and spaSim\n9:10 - 9:20\n\n\nReading and formatting image\n9:20 - 9:45\n\n\nQC and basic analysis\n9:45 - 10:05\n\n\nCell colocalisation\n10:05 - 10:35\n\n\nbreak\n10:35 - 10:45\n\n\nSpatial heterogeneity\n10:45 - 11:05\n\n\nTumour structure characterisation\n11:05 - 11:30\n\n\nNeighbourhood analysis\n11:30 - 11:45\n\n\nOverview of spaSim\n11:45 - 12:10\n\n\nQ & A\n12:10 - 12:30"
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-    "section": "Additional materials",
-    "text": "Additional materials\nPlease have a read of our recent paper if you are interested!\nLinks to the two packages:\n\nSPIAT Github and SPIAT Bioconductor\nspaSim Github and spaSim Bioconductor\n\nThese two R packages were developed in the Anna Trigos Lab."
   }
 ]
diff --git a/sitemap.xml b/sitemap.xml
@@ -2,14 +2,14 @@
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