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Shorten tutorial descriptions so they are not clipped on the cards (#299)
* Shorten tutorial descriptions so they are not clipped on the cards * Fix typo in the scRNA-seq category description * Reword the chromatin accessibility description
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tutorial-registry/categories.yml

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- scRNA-seq:
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description: |
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The following tutorials show show to analyze single-cell gene expression data.
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The following tutorials show how to analyze single-cell gene expression data.
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- Spatial:
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description: |

tutorial-registry/tutorials/ATAC-preprocessing/meta.yaml

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name: Processing chromatin accessibility
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description: |
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This chapter shows multimodal single-cell gene expression and
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chromatin accessibility analysis. In this notebook, scATAC-seq
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data processing is described.
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Chromatin accessibility processing in a joint RNA and ATAC analysis of 10k PBMCs.
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link: https://muon-tutorials.readthedocs.io/en/latest/single-cell-rna-atac/pbmc10k/2-Chromatin-Accessibility-Processing.html
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image: icon.png
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primary_category: ATAC-seq

tutorial-registry/tutorials/CITEseq-integration/meta.yaml

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name: CITE-seq integration
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description: |
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These notebooks showcase CITE-seq analysis of PBMCs with dsb
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normalization, MOFA+ data integration, and weighted nearest neighbors
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handling multimodal embeddings.
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CITE-seq analysis of PBMCs with dsb normalization, MOFA+ integration, and weighted nearest neighbors.
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link: https://muon-tutorials.readthedocs.io/en/latest/cite-seq/1-CITE-seq-PBMC-5k.html
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image: icon.png
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primary_category: Surface proteins

tutorial-registry/tutorials/Joint-analysis-of-multiomic-data-with-MultiVI/meta.yaml

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name: Joint analysis of paired and unpaired multiomic data with MultiVI
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description: |
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This tutorial shows how to read multiomic data, create a joint object with
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paired/unpaired data, train MultiVI model, visualize latent space,
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and run differential analyses.
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Read multiomic data, create a joint object from paired and unpaired data, train MultiVI, and run differential analyses.
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link: https://docs.scvi-tools.org/en/stable/tutorials/notebooks/multimodal/MultiVI_tutorial.html
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image: icon.png
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primary_category: ATAC-seq

tutorial-registry/tutorials/RNA-velocity/meta.yaml

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name: RNA velocity
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description: |
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This tutorial guides you through how RNA velocity can be inferred from single cell RNA-seq data
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using scVelo.
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Infer RNA velocity from single-cell RNA-seq data with scVelo.
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link: https://scvelo.readthedocs.io/en/stable/getting_started.html
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image: icon.png
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primary_category: scRNA-seq

tutorial-registry/tutorials/advanced-plotting/meta.yaml

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name: Advanced plotting
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description: |
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This tutorial explains how to customize matplotlib plots generated
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by scanpy or other scverse libraries.
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Customize matplotlib plots generated by scanpy or other scverse libraries.
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link: https://scanpy.readthedocs.io/en/stable/tutorials/plotting/advanced.html
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image: icon.png
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primary_category: Tips & Tricks

tutorial-registry/tutorials/anndata-getting-started/meta.yaml

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name: Getting started with AnnData
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description: |
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This tutorial helps you to explore the structure and content of single-cell
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data analysis results in a *.h5ad file using AnnData, Scanpy, and Python.
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Explore the structure and content of single-cell analysis results stored in an .h5ad file.
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link: https://scverse-tutorials.readthedocs.io/en/latest/notebooks/anndata_getting_started.html
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image: icon.svg
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primary_category: Data structures

tutorial-registry/tutorials/anndata-mudata-axes/meta.yaml

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name: Axes in AnnData and MuData
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description: |
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In this tutorial we showcase operations on independent AnnData objects
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(scRNAseq matrix + metadata), demonstrating how various processing
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workflows can be stored in one MuData object.
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Operations on independent AnnData objects, and how several processing workflows can live in one MuData object.
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link: https://scverse-tutorials.readthedocs.io/en/latest/notebooks/tutorial_axes_anndata_mudata.html
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primary_category: Data structures
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order: 20

tutorial-registry/tutorials/bentotools-subcellular-resolution/meta.yaml

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name: Spatial analysis with squidpy
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description: |
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This tutorial demonstrate how to use squidpy to analyse transcriptomics
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data with spatial resolution.
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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

tutorial-registry/tutorials/cellcharter-spatial-transcriptomics/meta.yaml

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name: Spatial clustering of spacial transcriptomics data with CellCharter
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description: |
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This tutorial demonstrate how to use CellCharter to cluster spatial transcriptomics data, obtained with the CosMx technology from Nanostring.
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This method can also be used for spatial proteomics data.
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Cluster spatial transcriptomics data from Nanostring CosMx with CellCharter. Also works for spatial proteomics.
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link: https://cellcharter.readthedocs.io/en/latest/notebooks/cosmx_human_nsclc.html
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image: icon.png
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primary_category: Spatial

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