sample_and_drop_adata_dict(adata_dict, ...)
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Sample each AnnData in adata_dict based on specified strata keys and drop strata with fewer than the minimum number of cells. |
normalize_adata_dict(adata_dict, **kwargs)
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Normalizes each AnnData in adata_dict using sc.pp.normalize_total(). |
log_transform_adata_dict(adata_dict, **kwargs)
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Log-transforms each AnnData in adata_dict using sc.pp.log1p(). |
set_high_variance_genes_adata_dict(...)
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Identifies highly variable genes in each AnnData in adata_dict using sc.pp.highly_variable_genes(). |
rank_genes_groups_adata_dict(adata_dict, ...)
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Identifies differentially expressed genes in each AnnData in adata_dict using sc.tl.rank_genes_groups(). |
scale_adata_dict(adata_dict, **kwargs)
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Scales each AnnData object in adata_dict using sc.pp.scale(). |
pca_adata_dict(adata_dict, **kwargs)
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Performs PCA on each AnnData object in adata_dict using sc.pp.pca(). |
neighbors_adata_dict(adata_dict, **kwargs)
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Calculates neighborhood graph for each AnnData object in adata_dict using sc.pp.neighbors(). |
leiden_adata_dict(adata_dict, **kwargs)
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Performs Leiden clustering for each AnnData object in adata_dict using Scanpy's leiden function. |
leiden_sub_cluster(adata, groupby, **kwargs)
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Perform Leiden clustering on subgroups of cells. |
leiden_sub_cluster_adata_dict(adata_dict, ...)
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Applies the leiden_sub_cluster() function to each AnnData object in adata_dict. |
calculate_umap_adata_dict(adata_dict, **kwargs)
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Calculates UMAP embeddings for each AnnData in adata_dict using sc.tl.umap(). |
plot_umap_adata_dict(adata_dict, **kwargs)
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Plots UMAP embeddings for each AnnData in adata_dict, colored by a specified variable. |
