simba.tl.infer_edges

simba.tl.infer_edges(adata_ref, adata_query, feature='highly_variable', n_components=20, random_state=42, layer=None, k=20, metric='euclidean', leaf_size=40, **kwargs)[source]

Infer edges between reference and query observations

Parameters:

  • adata_ref (AnnData) – Annotated reference data matrix.

  • adata_query (AnnData) – Annotated query data matrix.

  • feature (str, optional (default: None)) – Feature used for edges inference. The data type of .var[feature] needs to be bool

  • n_components (int, optional (default: 20)) – The number of components used in randomized_svd for comparing reference and query observations

  • random_state (int, optional (default: 42)) – The seed used for truncated randomized SVD

  • n_top_edges (int, optional (default: None)) – The number of edges to keep If specified, percentile will be ignored

  • percentile (float, optional (default: 0.01)) – The percentile of edges to keep

  • k (int, optional (default: 5)) – The number of nearest neighbors to consider within each dataset

  • metric (str, optional (default: ‘euclidean’)) – The metric to use when calculating distance between reference and query observations

  • layer (str, optional (default: None)) – The layer used to perform edge inference If None, .X will be used.

  • kwargs – Other keyword arguments are passed down to randomized_svd()

Returns:

adata_ref_query – Annotated relation matrix betwewn reference and query observations Store reference entity as observations and query entity as variables

Return type:

AnnData