tfmindi.pl.tsne

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tfmindi.pl.tsne#

tfmindi.pl.tsne(adata, color_by='leiden', alpha=0.2, s=2, show_legend=True, cmap='tab20', **kwargs)#

Visualize seqlet clusters in t-SNE space as a scatter plot.

Fast, lightweight function for data exploration without sequence logos. Ideal for quickly examining cluster structure and testing different coloring schemes.

Parameters:

  • adata (AnnData) – AnnData object with t-SNE coordinates and cluster assignments. Must contain adata.obsm[“X_tsne”] and adata.obs[“leiden”].

  • color_by (str (default: 'leiden')) – Column in adata.obs to use for coloring points (default: “leiden”).

  • alpha (float (default: 0.2)) – Transparency of scatter points.

  • s (float (default: 2)) – Size of scatter points.

  • show_legend (bool (default: True)) – Whether to show the legend (default: True).

  • cmap (str (default: 'tab20')) – Colormap name for categorical data (default: “tab20”). Any valid matplotlib colormap name (e.g., “viridis”, “plasma”, “Set1”).

  • **kwargs – Additional arguments passed to render_plot() for styling and display options. Common options include width, height, title, xlabel, ylabel, show, save_path.

Return type:

Figure | None

Returns:

matplotlib.Figure or None Figure with t-SNE scatter plot, or None if show=True.

Examples

>>> import tfmindi as tm
>>> # Basic t-SNE plot colored by clusters
>>> fig = tm.pl.tsne(adata, color_by="leiden")
>>> # Color by DNA-binding domain annotations
>>> tm.pl.tsne(adata, color_by="cluster_dbd", width=8, height=6)
>>> # Custom styling
>>> tm.pl.tsne(adata, color_by="leiden", alpha=0.8, s=30, title="Seqlet Clusters", show_legend=False)
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