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diff --git a/docs/no_toc/10c-spatial-transcriptomics.md b/docs/no_toc/10c-spatial-transcriptomics.md
@@ -24,6 +24,8 @@ Spatial transcriptomics (ST) technologies have been developed as a solution to t
 
 There is a large diversity in approaches to spatially profile tissues. Some ST technologies allow profiling at coarse cellular resolution, where regions of interest (ROIs) are usually identified by a pathologist. These ROIs may include tens of cells up to few hundreds (e.g., GeoMx @bergholtz2021best). Smaller ROI sizes can be found in other technologies such as Visium, where ROIs of 55uM of diameter (or "spots") often contain no more than 10 cells (<https://www.10xgenomics.com/resources/analysis-guides/integrating-single-cell-and-visium-spatial-gene-expression-data>). For finer cellular resolution, technologies such as MERFISH, SMI, or Xenium, among others, can measure gene expression at individual cells [@yue2023guidebook]. In general, there is a trade-off between the cellular resolution and molecular resolution, as the number of quantified genes and RNA molecules is lower in single-cell level spatial technologies compared to those at the ROI or spot level. In single-cell ST, often a panel of hundreds of genes is quantified, while in "mini-bulk" (ROI/spot) ST, it is possible to genes at the whole transcriptome level.
 
+<img src="resources/images/10c-spatial-transcriptomics_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g2668d07d0b9_461_0.png" title="A trade-off exists between the cellular resolution and molecular resolution in spatial transcriptomics." alt="A trade-off exists between the cellular resolution and molecular resolution in spatial transcriptomics." width="100%" />
+
 In addition to the differences in cellular and molecular, there are fundamental differences in the chemistry used to count the RNA transcripts in the tissue [@wang2021spatial; @yue2023guidebook]. Capture or hybridization of RNA followed by sequencing, or fluorescent imaging are two of the most common techniques used in ST methods. Because of large diversity in resolution and chemical procedures among ST technologies, data collection workflows are equally diverse. Finally, each study poses specific questions that cannot be addressed with traditional scRNA-seq pipelines, requiring customized workflows.
 
 Some of the commonalities in the workflows are presented here:

diff --git a/docs/no_toc/11d-CUT-and-RUN.md b/docs/no_toc/11d-CUT-and-RUN.md
diff --git a/docs/no_toc/404.html b/docs/no_toc/404.html
diff --git a/docs/no_toc/About.md b/docs/no_toc/About.md
@@ -39,7 +39,7 @@ These credits are based on our [course contributors table guidelines](https://gi
 ##  collate  en_US.UTF-8                 
 ##  ctype    en_US.UTF-8                 
 ##  tz       Etc/UTC                     
-##  date     2023-12-07                  
+##  date     2024-01-24                  
 ## 
 ## ─ Packages ───────────────────────────────────────────────────────────────────
 ##  package     * version date       lib source                            

diff --git a/docs/no_toc/a-very-general-genomics-overview.html b/docs/no_toc/a-very-general-genomics-overview.html
diff --git a/docs/no_toc/about-the-authors.html b/docs/no_toc/about-the-authors.html
diff --git a/docs/no_toc/annotating-genomes.html b/docs/no_toc/annotating-genomes.html
diff --git a/docs/no_toc/atac-seq-1.html b/docs/no_toc/atac-seq-1.html
diff --git a/docs/no_toc/bulk-rna-seq-1.html b/docs/no_toc/bulk-rna-seq-1.html
diff --git a/docs/no_toc/chip-seq-1.html b/docs/no_toc/chip-seq-1.html
diff --git a/docs/no_toc/chromatin-methods-overview.html b/docs/no_toc/chromatin-methods-overview.html
diff --git a/docs/no_toc/considerations-for-choosing-tools.html b/docs/no_toc/considerations-for-choosing-tools.html
diff --git a/docs/no_toc/cutrun-and-cuttag.html b/docs/no_toc/cutrun-and-cuttag.html
diff --git a/docs/no_toc/dna-methods-overview.html b/docs/no_toc/dna-methods-overview.html
diff --git a/docs/no_toc/dna-methylation-sequencing.html b/docs/no_toc/dna-methylation-sequencing.html
diff --git a/docs/no_toc/general-data-analysis-tools.html b/docs/no_toc/general-data-analysis-tools.html
diff --git a/docs/no_toc/guidelines-for-good-metadata.html b/docs/no_toc/guidelines-for-good-metadata.html
diff --git a/docs/no_toc/index.html b/docs/no_toc/index.html
diff --git a/docs/no_toc/index.md b/docs/no_toc/index.md
@@ -1,6 +1,6 @@
 ---
 title: "Choosing Genomics Tools"
-date: "December, 2023"
+date: "January, 2024"
 site: bookdown::bookdown_site
 documentclass: book
 bibliography: [book.bib]

diff --git a/docs/no_toc/introduction.html b/docs/no_toc/introduction.html
diff --git a/docs/no_toc/itcr--omic-tool-glossary.html b/docs/no_toc/itcr--omic-tool-glossary.html
diff --git a/docs/no_toc/microarray-data.html b/docs/no_toc/microarray-data.html
diff --git a/docs/no_toc/reference-keys.txt b/docs/no_toc/reference-keys.txt
@@ -314,15 +314,41 @@ tools-for-preprocessing
 tools-for-making-visualizations
 tools-for-making-heatmaps
 more-resources-about-chip-seq-data
-dna-methylation-sequencing
+cutrun-and-cuttag
 learning-objectives-17
+technologies
+advantages-of-cutrun-and-cuttag-over-the-traditional-chip-seq-technology
+cutrun-1
+autocutrun
+cuttag-1
+autocuttag
+cutac
+differences-between-cutrun-and-cuttag
+limitation-of-cutrun-and-cuttag
+general-data-analysis-workflow
+adapter-trimming
+alignment-1
+quality-control
+normalization
+spike-in-scaling
+sequencing-depth-and-coverage-normalization
+peak-calling-2
+seacr
+macs2
+seacr-vs-macs2
+fragment-proportion-in-peaks-regions-frips
+visualization-1
+differential-analysis
+more-resources-about-cutrun-and-cuttag-data-analysis
+dna-methylation-sequencing
+learning-objectives-18
 what-are-the-goals-of-analyzing-dna-methylation
 methylation-data-considerations
 beta-values-binomially-distributed
 measuring-5mc-andor-5hmc
 methylation-data-workflow
 methylation-tools-pros-and-cons
-quality-control
+quality-control-1
 analysis
 methylation-calling
 methylation-quantification

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diff --git a/docs/no_toc/rna-methods-overview.html b/docs/no_toc/rna-methods-overview.html
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