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method/Spatial-mgcn/Spatial-mgcn.yml
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| - torch_geometric==2.1.0 | ||
| - torch_sparse==0.6.15 | ||
| - torch_scatter==2.0.9 | ||
| - git+https://github.com/cs-wangbo/Spatial-MGCN@cf4412df6db6276e0c8a3f036ff0b1661adfdb35 |
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If it can be installed via pip why is the repo cloned during the run?
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It cannot be installed via pip. I updated the yml
method/Spatial-mgcn/Spatial-mgcn.py
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| # Normalize data: min_cells, calculate HVG and scale | ||
| sc.pp.filter_genes(adata, min_cells=100) | ||
| sc.pp.highly_variable_genes(adata, flavor="seurat_v3", n_top_genes=config["fdim"]) |
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Is there a reason not to use existing feature selection?
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I changed it to the existing feature selection now. But I left their feature selection as comments to make it easier to compare the performance of both ways.
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config/config_1.jsonwith hyperparameters for DLPFCCALC_ARItoTrueinSpatial-mgcn.py.CALC_ARI = True.