Last updated: 2025-11-28

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Knit directory: 2025_cytoconnect_spatial_workshop/

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Introduction

We can load the cluster annotation back to Qupath and visualise them.

Loading the clusters information to Qupath

First, we have to use some custom script to load the csv file to Qupath. Go to Automate -> Script Editor.

Copy the script that is in this Github link into the script editor. Then click run.

It’ll ask you to select the folder containing the csv file we exported in imc_02. Select the appropriate folder and click OK.

The script will run and load the cluster information to Qupath.

Visualising the clusters

To view the clusters, you need to first close the image and re-open it. Right click on the image, then select Multi-view -> Close viewer.

Go to the Project tab on the right panel, then click on the image all_channels.tif to re-open it.

The annotation list should now contain a new annotation called Clusters. Click on the triangle on the right of the class list panel and select Population from existing objects -> All classes (including sub-classes).

It’ll ask you whether you want to keep existing class or not, feel free to pick either option.

The class list should now contain the clusters we imported from R. This will allow you to select any given mask and assign it to a given cluster.

You can choose to show masks that are assigned to a given cluster by typing the cluster name in the search bar and click Select all button underneath it.

Pick a marker of your choice (e.g., FXIIIa) and visualise its expression across the selected clusters.


sessionInfo()
R version 4.5.1 (2025-06-13)
Platform: aarch64-apple-darwin20
Running under: macOS Sequoia 15.5

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: Australia/Perth
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] workflowr_1.7.2

loaded via a namespace (and not attached):
 [1] vctrs_0.6.5       httr_1.4.7        cli_3.6.5         knitr_1.50       
 [5] rlang_1.1.6       xfun_0.53         stringi_1.8.7     processx_3.8.6   
 [9] promises_1.3.3    jsonlite_2.0.0    glue_1.8.0        rprojroot_2.1.1  
[13] git2r_0.36.2      htmltools_0.5.8.1 httpuv_1.6.16     ps_1.9.1         
[17] sass_0.4.10       rmarkdown_2.29    jquerylib_0.1.4   tibble_3.3.0     
[21] evaluate_1.0.5    fastmap_1.2.0     yaml_2.3.10       lifecycle_1.0.4  
[25] whisker_0.4.1     stringr_1.5.2     compiler_4.5.1    fs_1.6.6         
[29] pkgconfig_2.0.3   Rcpp_1.1.0        rstudioapi_0.17.1 later_1.4.4      
[33] digest_0.6.37     R6_2.6.1          pillar_1.11.0     callr_3.7.6      
[37] magrittr_2.0.4    bslib_0.9.0       tools_4.5.1       cachem_1.1.0     
[41] getPass_0.2-4