scatrans.pl.comet_plot

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scatrans.pl.comet_plot#

scatrans.pl.comet_plot(df, top_n=12, save_path=None, title='Active Transcription Drivers', point_scale=1.0, min_size=2, max_size=180, s=None, alpha=0.85, figsize=(8, 6), dpi=300, fontsize=12, cmap='coolwarm', ax=None, show=True, use_style=False, positive_logfc_only=True, return_data=False, label_repel=True, label_fontsize=None, min_label_score=None)[source]#

Comet plot of log fold change vs. bias-corrected unspliced residual.

Point size and color are mapped to the active score. Designed to produce clear figures suitable for scientific publications with minimal further editing.

Size control (referencing common patterns in omicverse.pl.* for direct control):

  • s: if provided, use a fixed point size for all points (in points^2). This is the simplest way to make everything small (e.g. s=3 or s=1).

  • point_scale: overall multiplier for the variable size calculation.

  • min_size / max_size: hard bounds. Use min_size=1 to allow the tiniest background points when using variable sizing by active_score.

positive_logfc_only=True (default) keeps only logFC > 0 (classic “active drivers” comet view). Set False to see the full logFC vs residual scatter including negative logFC genes.

Returns:

  • (fig, ax) (always a matplotlib figure and axes. If no valid genes remain)

  • after coercion / filtering, returns a placeholder figure with a message

  • (instead of (None, None)) for better caller ergonomics.

Parameters:

  • ax (matplotlib.axes.Axes, optional) – If provided, plot into this axes instead of creating a new figure. Useful for embedding in multi-panel publication figures.

  • s (float | None)

  • alpha (float)

  • show (bool)

  • use_style (bool)

  • positive_logfc_only (bool)

  • return_data (bool)

  • label_repel (bool)

  • label_fontsize (float | None)

  • min_label_score (float | None)

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