stlearn.spatial.trajectory.detect_transition_markers_clades

stlearn.spatial.trajectory.detect_transition_markers_clades(adata: AnnData, clade: int, cutoff_spearman: float = 0.4, cutoff_pvalue: float = 0.05, screening_genes: None | list[str] = None, use_raw_count: bool = False) → None[source]

Transition markers detection of a clade.

Parameters:

  • adata (AnnData) – Annotated data matrix containing spatial transcriptomics data with computed pseudotime and clade information.

  • clade (int) – Numeric identifier of the clade for which to detect transition markers. Should correspond to a clade ID present in the trajectory analysis.

  • cutoff_spearman (float, default 0.4) – The minimum Spearman correlation coefficient threshold for identifying significant gene-pseudotime correlations. Must be between 0 and 1.

  • cutoff_pvalue (float, default 0.05) – The maximum p-value threshold for statistical significance testing. Must be between 0 and 1. Lower values result in more stringent statistical filtering.

  • screening_genes (list of str, optional) – Custom list of gene names to restrict the analysis to. If None, all genes in the dataset will be considered. Useful for focusing on specific gene sets or reducing computational time.

  • use_raw_count (bool, default False) – True if user wants to use raw layer data.

Returns:

The input AnnData object with additional information stored in adata.uns about the detected transition markers, including: - Correlation coefficients - P-values - Gene rankings - Clade-specific marker information

Return type:

AnnData