ocelli.tl.neighbors_graph

ocelli.tl.neighbors_graph(adata: AnnData, x: str, n_edges: int = 10, out: str = 'graph', verbose: bool = False, copy: bool = False)

Nearest neighbors-based graph construction

Constructs a nearest neighbors-based graph from a precomputed nearest neighbors search. Each graph node (cell) is connected to n_edges nearest neighbors in the embedding space.

Note

Before using this function, you must run ocelli.pp.neighbors to compute the nearest neighbors for the specified embedding.

Parameters:

• adata (anndata.AnnData) – The annotated data matrix.

• x (str) – Key in adata.obsm corresponding to the embedding for which nearest neighbors were computed.

• n_edges (int) – Number of edges (connections) per graph node. (default: 10)

• out (str) – Key in adata.obsm where the constructed graph is saved. (default: ‘graph’)

• verbose (bool) – Whether to print progress notifications. (default: False)

• copy (bool) – Whether to return a copy of adata. If False, updates are made in-place. (default: False)

Returns:

• If copy=False: Updates adata with the constructed graph stored in adata.obsm[out].

• If copy=True: Returns a modified copy of adata with the constructed graph.

Return type:

anndata.AnnData or None

Example:

import ocelli as oci
from anndata import AnnData
import numpy as np

# Example data
adata = AnnData(X=np.random.rand(100, 50))
adata.obsm['embedding'] = np.random.rand(100, 10)

# Compute nearest neighbors
oci.pp.neighbors(adata, x=['embedding'], n_neighbors=20)

# Construct nearest neighbors-based graph
oci.tl.neighbors_graph(adata, x='embedding', n_edges=10, verbose=True)