Merge branch 'read_data' of github.com:dcgc-bfx/spatial-analysis-xenium-training into read_data

Author: ulrikefriedrich

.gitignore

@@ -0,0 +1,9 @@
+*.Rproj
+*.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+/.quarto/
+**/*.quarto_ipynb
+datasets/
+.Rproj.user

README.md

@@ -1,10 +1,10 @@
-![Banner](docs/spatial_banner.png)
+![Banner](docs/Xenium_banner.png)
 
-# Analysis of Spatial Transcriptomics Data (Visium HD)
+# Analysis of Spatial Transcriptomics Data (Xenium)
 
-Welcome to our **hands-on workbook collection** to learn spatial transcriptomics data analysis, with a focus on 10x Genomics Visium HD data!
+Welcome to our **hands-on workbook collection** to learn spatial transcriptomics data analysis, with a focus on 10x Genomics Xenium data!
 
-Spatial transcriptomics allows us to measure gene expression across tissue sections while preserving spatial information, helping us understand not just **what** genes are active, but **where** they are active.
+Spatial transcriptomics allows us to measure gene expression across tissue sections while preserving spatial information, helping us understand not just **which** genes are active, but also **where** they are active.
 
 With our workbooks, you will explore how to analyze spatial transcriptomics data using **R** and **RStudio**. Whether you're new to spatial data or already familiar with single-cell workflows, our guides will walk you through the essential steps.
 
@@ -16,18 +16,18 @@ With our workbooks, you will explore how to analyze spatial transcriptomics data
 - [Citation](#citation)
 - [Quick Start](#quick-start-)
 
-## Workbooks overview 📘
+## Workbooks overview
 
 Our workbooks cover:
 
-- Learn how to load spatial data into R and examine how the data is structured
-- Key steps in the analysis workflow, including quality control, preprocessing, clustering and visualisation, cluster annotation, spatial clustering, and integration with single-cell transcriptomics data.
+- Learn how to [load spatial data into R](workbooks/read_dataset_to_seurat.qmd) and examine how the data is structured
+- Key steps in the [analysis workflow](workbooks/analyze_spatial_dataset.qmd), including quality control, preprocessing, clustering and visualisation, cluster annotation, spatial clustering, and reference mapping.
 
-## Credits 👥
+## Credits
 
-The workbooks are being written by [Katrin Sameith](https://github.com/ktrns) and [Andreas Petzold](https://github.com/andpet0101) at the [DRESDEN-concept Genome Center](https://genomecenter.tu-dresden.de/about-us). 
+The workbooks are being written by [Katrin Sameith](https://github.com/ktrns), [Andreas Petzold](https://github.com/andpet0101), [Ulrike Friedrich](https://github/ulrikefriedrich), and [Rajinder Gupta](https://github.com/rajinder4489) at the [DRESDEN-concept Genome Center](https://genomecenter.tu-dresden.de/about-us). 
 
-## Contributions 🤝
+## Contributions
 
 We welcome contributions! To contribute:
 
@@ -39,49 +39,5 @@ We welcome contributions! To contribute:
 
 If you used our workbooks to analyze your data, please cite it by mentioning the DRESDEN-concept Genome Center URL "https://genomecenter.tu-dresden.de". 
 
-## Quick Start 🚀
-
-On a linux laptop, you can get started right away using our containerized environment:
-
-```bash
-# Clone the repository
-git clone git@github.com:dcgc-bfx/2025-ngs-cn-summer-school.git
-
-# Container image
-SINGULARITY_IMAGE=oras://gcr.hrz.tu-chemnitz.de/dcgc-bfx/singularity/singularity-single-cell:Unstable
-
-# Set user, password and port
-export SINGULARITYENV_RSTUDIO_USER=$(whoami)
-export SINGULARITYENV_RSTUDIO_PASSWORD="verysecret"
-export SINGULARITYENV_RSTUDIO_PORT=9999
-
-# Define temporary directory
-workdir=...
-mkdir -p ${workdir}/singularity ${workdir}/tmp ${workdir}/rserver
-
-# Start R-Server
-singularity exec \
-  --cleanenv \
-  --scratch /run,/var/lib/rstudio-server \
-  --workdir ${workdir}/singularity \
-  --bind ${workdir}/tmp \
-  --bind ${workdir}/rserver \
-  ${SINGULARITY_IMAGE} \
-  micromamba run --name single-cell /usr/lib/rstudio-server/bin/rserver --server-user=${SINGULARITYENV_RSTUDIO_USER} --www-port=${SINGULARITYENV_RSTUDIO_PORT}
-```
-
-Once you have started Rstudio with our container, you can start your analysis. 
-
-- Open your web browser (we recommend Chrome or Firefox).
-- Navigate to:  
-  - `localhost:${SINGULARITYENV_RSTUDIO_PORT}`
-- Log in with the credentials:  
-  - Username: `${SINGULARITYENV_RSTUDIO_USER}`  
-  - Password: `${SINGULARITYENV_RSTUDIO_PASSWORD}`
-- Download required datasets with the `datasets/download.R` script
-- Open `workbooks/read_dataset_to_seurat.qmd`
-
-You're now ready to explore the workbooks in a fully configured RStudio environment!
-
 **Happy coding & exploring spatial data!**
 

_quarto.yml

@@ -2,7 +2,6 @@ project:
   type: "default"
   execute-dir: "project"
   render:
-    - "workbooks/our_first_workbook.qmd"
     - "workbooks/read_dataset_to_seurat.qmd"
     - "workbooks/analyze_spatial_dataset.qmd"
 
@@ -12,26 +11,30 @@ project:
 execute: 
   echo: true
   warning: false
+  message: false
 
 #################
 # Knitr options #
 #################
 knitr:
   opts_chunk:
-    dpi: 400
+    timeit: true
+    dpi: 200
     fig-width: 8
     fig-height: 5
     dev:
     - "png"
     dev.args:
       png:
         type: "cairo"
-    
+
 ##################
 # Format options #
 ##################
 format:
   html:
+    toc: true
+    toc-location: left
     theme:
     - "serif"
     - "css/html.scss"

datasets/download.R

@@ -10,7 +10,7 @@ curl::curl_download(url="https://cf.10xgenomics.com/samples/xenium/3.0.0/Xenium_
                     destfile="datasets/Xenium_Prime_Mouse_Brain_Coronal_FF_outs.zip")
 unzip(zipfile="datasets/Xenium_Prime_Mouse_Brain_Coronal_FF_outs.zip", exdir="datasets/xenium_mouse_brain")
 unlink("datasets/Xenium_Prime_Mouse_Brain_Coronal_FF_outs.zip")
-untar("datasets/xenium_mouse_brain/cell_feature_matrix.tar.gz", exdir="output_dir")
+untar("datasets/xenium_mouse_brain/cell_feature_matrix.tar.gz", exdir="datasets/xenium_mouse_brain/")
 
 
 # Download H&E images
@@ -19,3 +19,15 @@ curl::curl_download(url="https://cf.10xgenomics.com/samples/xenium/3.0.0/Xenium_
 curl::curl_download(url="https://cf.10xgenomics.com/samples/xenium/3.0.0/Xenium_Prime_Mouse_Brain_Coronal_FF/Xenium_Prime_Mouse_Brain_Coronal_FF_he_imagealignment.csv", 
                     destfile="datasets/xenium_mouse_brain/Xenium_Prime_Mouse_Brain_Coronal_FF_he_imagealignment.csv")
 
+
+# Allen Brain Atlas from Seurat Visium HD vignette. Seurat object. Reduced to 200,000 cells (and rare cell types <25 cells have been removed).
+curl::curl_download(url="https://www.dropbox.com/scl/fi/r1mixf4eof2cot891n215/allen_scRNAseq_ref.Rds?rlkey=ynr6s6wu1efqsjsu3h40vitt7&dl=1",
+                     destfile="datasets/allen_scRNAseq_ref.Rds")
+
+# Pre-computed SpaNorm data
+h = curl::new_handle()
+curl::handle_setopt(handle=h, userpwd="XpC3kSoZQqt2kYK:1234")
+curl::handle_setheaders(h, "X-Requested-With"="XMLHttpRequest")
+curl::curl_download(url="https://datashare.tu-dresden.de/public.php/webdav/",
+                    destfile="datasets/spanorm.rds",
+                    handle=h)