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@PhilippStaedter @ngocphuongtran @julianalbers

I added you tot he squidpy repo, you should have received an invite. To install it, it's very similar for scanpy

git clone https://github.com/theislab/squidpy.git
cd squidpy
pip install -e'.[dev,test]'

I will write the functions needed in the respective issues. If there are missing libraries for your specific purpose, just write here the error messate.

• download a data of choice from 10x genomics with sc.datasets_visium_sge() (you can browse them here)
• run the scanpy tutorial, similar to here: https://scanpy-tutorials.readthedocs.io/en/latest/spatial/basic-analysis.html
• potentially save clustering results at different resolutions, for example

for res in [0.5,0.7,1]:
	sc.tl.leiden(adata, resolution=res, key_added = f"leiden_{res}")

• import large tiff image with imageio.imread(PATH) (pip install imageio)
• understand a bit how spatial coordinates relate to image pixels (have a look at respective nb in this repo)

Then we'll discuss next week about extracting patches from this image with our squidpy package.

@PhilippStaedter

you can find a processed anndata from this paper: https://www.biorxiv.org/content/10.1101/2020.10.26.354829v1

at login3 in ~/spatial_data folder

• download a data of choice from 10x genomics with sc.datasets_visium_sge() (you can browse them here)
• run the scanpy tutorial, similar to here: https://scanpy-tutorials.readthedocs.io/en/latest/spatial/basic-analysis.html
• compare marker genes in spatial dataset with marker genes in immune atlas (Scanpy function is sc.tl.rank_genes_group

Then we'll discuss next week about ligand-receptor interaction analysis with our squidpy package.

Have a look at analysis done here, potentially interesting for you: https://www.biorxiv.org/content/10.1101/2021.01.02.425073v1.full

@julianalbers

• download a data of choice from 10x genomics (you can browse them here)
  • find a way to load them in R with this
  • otherwise, download them and load them in python with sc.datasets_visium_sge()
• run a tutorial for data analysis
  • in R: https://satijalab.org/seurat/v3.2/spatial_vignette.html
  • in python: https://scanpy-tutorials.readthedocs.io/en/latest/spatial/basic-analysis.html
• at the end of the analysis, make sure you have run differntial expression analysis
  • if in python, the function is: sc.tl.rank_genes_group

Then we'll discuss next week about spatial statistics tools. In R you can try this: https://github.com/xzhoulab/SPARK

@ngocphuongtran