tfmindi.pl.dbd_topic_heatmap

tfmindi.pl.dbd_topic_heatmap#

tfmindi.pl.dbd_topic_heatmap(adata, cluster_column='leiden', dbd_column='cluster_dbd', vmax=0.01, cmap='RdPu', show_labels=True, **kwargs)#

Plot heatmap of average topic probabilities grouped by DNA-binding domain (DBD).

This shows how different DBD families are associated with specific topics.

Parameters:

  • adata (AnnData) – AnnData object containing cluster and DBD annotations in .obs and stored topic modeling results

  • cluster_column (str (default: 'leiden')) – Column name in adata.obs containing cluster assignments

  • dbd_column (str (default: 'cluster_dbd')) – Column name in adata.obs containing DBD annotations per cluster

  • vmax (float (default: 0.01)) – Maximum value for colormap

  • cmap (str (default: 'RdPu')) – Colormap name

  • show_labels (bool (default: True)) – Whether to show axis labels

  • **kwargs – Additional arguments passed to render_plot()

Return type:

Figure | None

Returns:

matplotlib Figure or None if show=False

Examples

>>> import tfmindi as tmi
>>> # After clustering and topic modeling
>>> tm.tl.run_topic_modeling(adata, n_topics=40)
>>> fig = tmi.pl.dbd_topic_heatmap(adata)