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Drop the bento-tools entry and fold cell-cell communication into scRNA-seq (#300)
The bento entry linked to the docs homepage rather than a tutorial. Its directory was also named squidpy-spatial while holding the bento tutorial, and the squidpy tutorial sat in bentotools-subcellular-resolution, so the remaining squidpy entry moves into the correctly named directory. Cell-cell communication was the only category classifying by analysis type rather than modality, and scRNA-seq already holds analysis-type tutorials such as RNA velocity and pseudotime.
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tutorial-registry/categories.yml

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

tutorial-registry/schema.json

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"scRNA-seq",
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"Spatial",
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"Adaptive immune cell receptor",
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"Cell-cell communication",
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"Surface proteins",
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"ATAC-seq",
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"Multimodal",
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tutorial-registry/tutorials/bentotools-subcellular-resolution/meta.yaml

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

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Infer ligand-receptor interactions between cell types and aggregate the methods into a consensus ranking.
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link: https://liana-py.readthedocs.io/en/latest/notebooks/basic_usage.html
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image: icon.png
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primary_category: Cell-cell communication
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order: 10
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primary_category: scRNA-seq
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order: 120
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modality:
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- RNA
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tags:
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name: Spatial analysis at subcellular resolution
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name: Spatial analysis with squidpy
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description: |
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Study gene expression at subcellular resolution with bento-tools.
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link: https://bento-tools.readthedocs.io/en/latest/index.html
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Analyse transcriptomics data with spatial resolution using squidpy.
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link: https://squidpy.readthedocs.io/en/latest/notebooks/tutorials/tutorial_vizgen_mouse_liver.html
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image: icon.png
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primary_category: Spatial
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order: 30
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order: 10
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tags:
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- preprocessing
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- visualization
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packages:
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- bento-tools
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- squidpy
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authors:
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- ckmah
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- giovp

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