bento.tl.fe

bento.tl.fe(sdata, net, instance_key='cell_boundaries', source='source', target='target', weight='weight', batch_size=10000, min_n=0)

Perform functional enrichment of RNAflux embeddings. Uses decoupler wsum function.

Parameters:

  • sdata (SpatialData) – Spatial formatted SpatialData object.

  • net (DataFrame) – DataFrame with columns “source”, “target”, and “weight”. See decoupler API for more details.

  • source (str, optional) – Column name for source nodes in net. Default “source”.

  • target (str, optional) – Column name for target nodes in net. Default “target”.

  • weight (str, optional) – Column name for weights in net. Default “weight”.

  • batch_size (int) – Number of points to process in each batch. Default 10000.

  • min_n (int) – Minimum number of targets per source. If less, sources are removed.

Returns:

sdata –

.points[“cell_boundaries_raster”][“flux_fe”]DataFrame

Enrichment scores for each gene set.

Return type:

SpatialData