Tools (sch.tl)

The tools module provides analysis functions for energy, networks, correlations, embeddings, Jacobians, and velocity.

Energy Analysis

`compute_energies`(adata[, spliced_key, ...])	Calculate energy landscapes for all clusters.
`decompose_degradation_energy`(adata, cluster)	Calculate gene-wise degradation energy decomposition.
`decompose_bias_energy`(adata, cluster[, ...])	Calculate gene-wise bias energy decomposition.
`decompose_interaction_energy`(adata, cluster)	Calculate gene-wise interaction energy.

`network_correlations`(adata[, cluster_key, copy])	Compute various similarity metrics between cluster interaction networks.
`get_network_links`(adata[, cluster_key, ...])	Extract network links (edges) from interaction matrices.
`compute_network_centrality`(adata[, ...])	Compute network centrality metrics for genes in each cluster.
`get_top_genes_table`(adata, metric[, ...])	Create formatted table with top genes per cluster for a given metric.
`compute_eigenanalysis`(adata[, cluster_key, copy])	Compute eigenvalue decomposition for each cluster's interaction matrix.
`get_top_eigenvector_genes`(adata, cluster[, ...])	Get top genes from eigenvector corresponding to extreme eigenvalue.
`get_eigenanalysis_table`(adata[, ...])	Create formatted table with top genes from extreme eigenvectors.

`energy_gene_correlation`(adata[, ...])	Correlate energies with gene expression.
`celltype_correlation`(adata[, spliced_key, ...])	Compute correlation between cell types based on gene expression.
`future_celltype_correlation`(adata[, ...])	Compute correlation between cell types based on predicted future states.
`get_correlation_table`(adata[, cluster_key, ...])	Get correlation table with top genes per cluster.

`compute_umap`(adata[, spliced_key, ...])	Compute UMAP embedding from gene expression data.
`energy_embedding`(adata[, basis, resolution, ...])	Compute energy landscape on 2D embedding space.
`save_embedding`(adata, filename)	Save UMAP embedding and energy grid data to file.
`load_embedding`(adata, filename[, basis, copy])	Load UMAP embedding and energy grid data from file.

`compute_jacobians`(adata[, spliced_key, ...])	Compute Jacobian matrices and eigenvalues for all cells.
`save_jacobians`(adata, filename[, ...])	Save Jacobian eigenvalues and eigenvectors to HDF5 file.
`load_jacobians`(adata, filename[, ...])	Load Jacobian eigenvalues and optionally eigenvectors from HDF5 file.
`compute_jacobian_stats`(adata[, filename, ...])	Compute summary statistics from Jacobian eigenvalues.
`compute_jacobian_elements`(adata, gene_pairs)	Compute specific Jacobian matrix elements (partial derivatives).
`compute_rotational_part`(adata[, ...])	Compute the rotational (antisymmetric) part of the Jacobian.

`compute_reconstructed_velocity`(adata[, ...])	Compute reconstructed velocity from Hopfield model.
`validate_velocity`(adata[, velocity_key, ...])	Validate reconstructed velocity against original velocity.