Drop the bento-tools entry and fold cell-cell communication into scRNA-seq

tutorial-registry/categories.yml

@@ -16,10 +16,6 @@
     description: |
       Tutorials for analyzing single-cell B-cell and T-cell receptor sequencing data
 
-- Cell-cell communication:
-    description: |
-      Infer and analyse interactions between cells
-
 - Surface proteins:
     description: |
       CITE-seq analyses

tutorial-registry/schema.json

@@ -31,7 +31,6 @@
                 "scRNA-seq",
                 "Spatial",
                 "Adaptive immune cell receptor",
-                "Cell-cell communication",
                 "Surface proteins",
                 "ATAC-seq",
                 "Multimodal",

tutorial-registry/tutorials/liana-ligand-receptor/meta.yaml

@@ -3,8 +3,8 @@ description: |
   Infer ligand-receptor interactions between cell types and aggregate the methods into a consensus ranking.
 link: https://liana-py.readthedocs.io/en/latest/notebooks/basic_usage.html
 image: icon.png
-primary_category: Cell-cell communication
-order: 10
+primary_category: scRNA-seq
+order: 120
 modality:
   - RNA
 tags:

tutorial-registry/tutorials/squidpy-spatial/meta.yaml

@@ -1,14 +1,14 @@
-name: Spatial analysis at subcellular resolution
+name: Spatial analysis with squidpy
 description: |
-  Study gene expression at subcellular resolution with bento-tools.
-link: https://bento-tools.readthedocs.io/en/latest/index.html
+  Analyse transcriptomics data with spatial resolution using squidpy.
+link: https://squidpy.readthedocs.io/en/latest/notebooks/tutorials/tutorial_vizgen_mouse_liver.html
 image: icon.png
 primary_category: Spatial
-order: 30
+order: 10
 tags:
   - preprocessing
   - visualization
 packages:
-  - bento-tools
+  - squidpy
 authors:
-  - ckmah
+  - giovp