pyXenium.contour.compare_contour_transcript_de

compare_contour_transcript_de(sdata, *, contour_key, groupby, contour_query=None, cell_query=None, transcript_query=None, feature_key='gene_name', genes=None, assignment='coordinates', comparisons=('global', 'one_vs_rest'), case=None, reference=None, min_total_transcripts_per_contour=1, min_contours_per_group=2, include_zero_counts=False, return_contour_gene=True)

Compare contour groups with transcript-count pseudobulk normalization.

Transcript coordinates are assigned directly to contour polygons, converted to contour x gene counts, normalized as CPM and log1p(CPM), and compared across contour groups. By default transcripts are assigned by their x/y coordinates. Set assignment="cell_id" to aggregate cell-associated transcripts through the contour membership of each cell centroid, which is useful for whole-transcriptome screening. Set return_contour_gene=False for whole-transcriptome scans where the full contour-gene long table would be unnecessarily large.

Parameters:

• sdata (XeniumSlide)

• contour_key (str)

• groupby (str)

• contour_query (str | None)

• cell_query (str | None)

• transcript_query (str | None)

• feature_key (str)

• genes (str | Sequence[str] | None)

• assignment (str)

• comparisons (str | Sequence[str])

• case (str | Sequence[str] | None)

• reference (str | Sequence[str] | None)

• min_total_transcripts_per_contour (int)

• min_contours_per_group (int)

• include_zero_counts (bool)

• return_contour_gene (bool)

Return type:

dict[str, DataFrame]