hucira.plot_significant_results

hucira.plot_significant_results#

hucira.plot_significant_results(results_pivot, df_annot, robust_results_dict=None, selected_celltypes=None, selected_cytokines=None, fontsize=6.0, save_fig=False, fig_path='', fig_width=10.0, fig_height=12.0)#

Plot a heatmap of robust enrichment results.

Plots either the robust results from a dict of contrasts or individually per contrast.

Parameters:

  • results_pivot (pandas.DataFrame) – Pivot DataFrame of robust enrichment scores for one contrast.

  • df_annot (pandas.DataFrame) – Annotation DataFrame of significance stars for one contrast.

  • robust_results_dict (dict or None) – Robust enrichment score dictionary from get_robust_significant_results(). If provided, takes precedence over results_pivot and df_annot.

  • selected_celltypes (list of str or None) – Subset of cell types to visualise.

  • selected_cytokines (list of str or None) – Subset of cytokines to visualise.

  • fontsize (float) – Font size for annotations and tick labels.

  • save_fig (bool) – Whether to save the figure to disk.

  • fig_path (str) – Directory for saved figures.

  • fig_width (float) – Figure width in inches.

  • fig_height (float) – Figure height in inches.

Return type:

None

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